СПОСОБ И СИСТЕМА ДЛЯ ОПТИКО-ИНЕРЦИАЛЬНОГО ТРЕКИНГА ПОДВИЖНОГО ОБЪЕКТА

Изобретение относится к способу и системе для обратного оптико-инерциального трекинга подвижного объекта. Способ включает в себя следующие шаги: (а) обеспечивают излучение множеством маркеров света в ИК-диапазоне; (б) посредством первого устройства обработки данных считывают изображение с оптического датчика, физически связанного с подвижным объектом, и выявляют в считанном изображении пиксели, соответствующие заранее заданным условиям; (в) на основе выявленных пикселей посредством первого устройства обработки данных выявляют изображения маркеров и определяют параметры этих изображений маркеров; (г) посредством первого устройства обработки данных считывают данные с, по меньшей мере, одного инерциального датчика, физически связанного с подвижным объектом; (д) посредством первого устройства обработки данных формируют объединенный поток данных, содержащий параметры изображений маркеров и данные с упомянутого, по меньшей мере, одного инерциального датчика, и посредством первого устройства связи ...

Inertial navigation accuracy enhancement

Apparatus for the improvement of inertial navigation system (INS) position/velocity comprises frame stores 14, 16 for storing sequential images from a video camera 10 and a comparator 22, 26 for comparing pixels in predicted images, derived from earlier stored images as modified by INS linear and angular velocity outputs A5, A6, with pixels in actual later stored images, to derive a velocity error correction signal 28 which is used to correct the INS output. The video processing correction system described is passive and hence does not reveal the aircraft's whereabouts as would be the case with other positional correction systems using radar, nor does it rely on systems outside the control of the INS e.g. GPS, nor is it reliant on a vast terrain feature database.

System and method for enhancing non-inertial tracking system with inertial constraints

A position and orientation of a device 100 is found by estimating a first tracking state of the device using measurements from an exteroceptive sensor (ES) 104 such as a camera, sampled at a first rate. A second tracking state of the device is found using measurements from an inertial measurement unit (IMU) 106 sampled at a second rate asynchronous to the first rate. The first and second tracking states are synchronised by estimating a time offset that minimizes an error between changes over time between the first and second tracking states. The first tracking state and the second tracking state are aligned to an inertial reference frame. An inertial-aided tracking state is generated by minimizing a cost function that includes a first residual term derived from propagating a previous state estimate using the second tracking state shifted by the time offset and a second residual term derived from the first tracking state. In further aspects of the invention, the tracking state is an orientation ...

Using optical sensors to resolve vehicle heading issues

A control system (100) fuses different sensor data together to determine an orientation of a vehicle (50). The control system (100) receives visual heading data for the vehicle (50) from a camera system (102), global navigation satellite system (GNSS) heading data from a GNSS system (108), and inertial measurement unit (IMU) heading data from an IMU (110). The control system (100) may assign weights to the visual, GNSS, and IMU heading data based on operating conditions of the vehicle (50) that can vary accuracy associated with the different visual, GNSS, and IMU data. The control system (100) then uses the weighted visual, GNSS, and IMU data to determine a more accurate vehicle heading.

IMAGE DISPLAY METHOD AND ELECTRONIC DEVICE

This application provides example image display methods, media, and electronic devices . One example method includes detecting, by an electronic device that has a camera and a display, an operation of opening experience data by a user, where the experience data is stored in the electronic device and includes video data, and the video data includes multiple frames of images. A first interface is displayed in response to the operation, where the first interface includes a first image. Pose change information is determined within a preset duration, where the pose change information includes location movement information of the electronic device and pose change information of the camera. A second image including digital signage or a 3D virtual object is displayed based on pose data during collection of the first image and based on the pose change information, where the multiple frames of images include the second image.

SYSTEMS AND METHODS FOR DETECTION OF FEATURES WITHIN DATA COLLECTED BY A PLURALITY OF ROBOTS BY A CENTRALIZED SERVER

Navigationsvorrichtung und Verfahren zum Navigieren eines Transportmittels

Angegeben wird Navigationsvorrichtung (100) für ein Transportmittel, welche eine Sensoreinrichtung (102), eine Verarbeitungseinrichtung (104a) und eine Positionserfassungseinrichtung (103) aufweist, wobei die Sensoreinrichtung (102) zum Erfassen eines Umgebungsparameters eingerichtet ist,dadurch gekennzeichnet, dassdie Positionserfassungseinrichtung (103) eingerichtet ist, das Passieren einer geographischen Bereichsgrenze (107) durch das Transportmittel zu erkennen, die Verarbeitungseinrichtung (104a) eingerichtet ist, nach dem Erkennen des Passierens der geographischen Bereichsgrenze (107) eine Ausrichtung (108) der Sensoreinrichtung (102) zu verändern, mittels der Sensoreinrichtung (102) eine vorgebbare Markierung (112a, 112b, 112c) in einem vorgebbaren Suchbereich zu suchen; und das Transportmittel (101) beim Erkennen der vorgebbaren Markierung (112a, 112b, 112c) entlang dieser vorgebbaren Markierung (112a, 112b, 112c) zu bewegen.

PROCEDURE FOR HIGHLY SOLUBLE ONE 3D-BILDGEBUNG

ERROR CORRECTION OF AIRBORNE VEHICLES USING NATURAL PATTERNS

Disclosed are systems and methods for in-transit or in-flight error correction in state prediction of the vehicle. Natural patterns, such as fields, residential neighborhoods, business areas (e.g., downtown), etc., and/or objects, such as streets, cars, houses, trees, buildings, bridges, roads, parking lots, etc., that are naturally within the environment may be determined and used to correct any error in the aerial vehicle state prediction, while the vehicle is in transit, thereby eliminating or reducing the cumulative error involved in traditional systems.

Autonomous Platform Guidance Systems with Task Planning and Obstacle Avoidance

The described positional awareness techniques employing sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to find new area to cover by a robot encountering an unexpected obstacle traversing an area in which the robot is performing an area coverage task. The sensory data are gathered from an operational camera and one or more auxiliary sensors.

METHOD AND DEVICE FOR DISPLAYING DATA FOR MONITORING EVENT

An augmented reality method includes acquisition of a plurality of images by an image acquisition device that at least partially cover a space that has at least two landmarks. A three-dimensional position and orientation of the space in relation to the image acquisition device is determined. The instantaneous position, within the reference frame of the space, of a mobile element moving in the space is received. At least one acquired image is displayed on the screen. An overlay is superposed on the displayed image at a predetermined distance in relation to the position of the mobile element in the image. Also, a portable electronic device implements the method. 115-. (canceled)16. An augmented reality method in real time , comprising:acquiring a plurality of images by an image acquisition device that at least partially cover a space, the space comprising at least two landmarks, the image acquisition device being associated with a two-dimensional reference frame, referred to as a reference frame of the image, the image acquisition device being comprised in a portable electronic device comprising a screen;detecting said at least two landmarks of the space in at least one image, the space being associated with a three-dimensional reference frame, referred to as a reference frame of the space;determining a three-dimensional position and orientation of the space in relation to the image acquisition device based on said at least two landmarks detected;receiving an instantaneous position, within the reference frame of the space, of a mobile element moving in the space;calculating a position of the mobile element in the reference frame of the image from transformation parameters between the reference frame of the space and the reference space of the image, the transformation parameters being calculated from the three-dimensional position and orientation of the space in relation to the image acquisition device;displaying at least one acquired image on the screen; ...

Electronic device for generating map data and operation method thereof

Provided are an electronic device for generating map data and an operating method of the electronic device. The operating method of the electronic device includes: obtaining image data of a first resolution and image data of a second resolution for each of a plurality of nodes generated while the electronic device moves; obtaining location information with respect to each of the generated nodes, by using the image data of the second resolution; generating and storing map data by matching the obtained location information with the image data of the first resolution for each node; and estimating a current location of the electronic device by using the generated map data and the image data of the first resolution.

SYSTEMS AND METHODS USING IMAGE PROCESSING TO DETERMINE AT LEAST ONE KINEMATIC STATE OF A VEHICLE

System and methods are described that illustrate how to more accurately determine at least one state variable of a vehicle using imaging of a travel way line. Imaging can be used to determine an angle between a longitudinal axis of the travel way line and a longitudinal axis of the vehicle, a shortest distance between the center axis and a reference point on or in the vehicle, and corresponding errors. The determined angle, the determined distance, and the corresponding errors can be used to more accurately determine the at least one state variable.

СПОСОБ ЛОКАЛИЗАЦИИ РОБОТА В ПЛОСКОСТИ ЛОКАЛИЗАЦИИ

Изобретение касается способа локализации человекоподобного робота в плоскости локализации, связанной с двумерным ориентиром с двумя осями x и y. Способ включает следующие этапы: определение (200) посредством одометрии оценки координат x1 и y1 робота, а также оценки его ориентации Ө1; определение (202) оценки Ө2 ориентации робота посредством использования виртуального компаса; определение (204) оценки Ө3 ориентации робота посредством корреляции частей опорной панорамы с частями панорамы запроса; определение (206) оценки x4, y4 положения робота посредством использования итерационной технологии ближайших точек; определение средних квадратичных отклонений σ_x1, σ_x2, σ_Ө1, σ_Ө2, σ_Ө3, σ_x4, σ_y4 упомянутых выше оценок; определение (220) распределений G(x1), G(y1), G(Ө1), G(Ө2), G(Ө3), G(x4) и G(y4) вероятностей каждой доступной оценки с использованием упомянутых средних квадратичных отклонений; определение (221) трех глобальных распределений GLOB(x), GLOB(y) и GLOB(Ө) и определение глобальной ...

VERFAHREN UND VORRICHTUNG ZUR PARALLELEN VERFOLGUNG UND LOKALISIERUNG MITTELS EINES MULTIMODALEN SCHMELZVERFAHRENS

Ein Verfahren zur Fahrzeugverfolgung und -lokalisierung umfasst das Empfangen von Odometrie-Daten von einem Sensor des ersten Fahrzeugs durch eine Steuerung, von georäumliche Daten von einer GPS-Vorrichtung (Global Positioning System) des ersten Fahrzeugs, von Inertial-Daten von einer Inertial-Messeinheit (IMU) des ersten Fahrzeugs, das Abschätzen einer geschätzten aktuellen Position des ersten Fahrzeugs und einer geschätzten aktuellen Trajektorie des ersten Fahrzeugs unter Verwendung der Odometrie-Daten vom Sensor, der georäumliche Daten von der GPS-Vorrichtung und der Inertial-Daten von der IMU des ersten Fahrzeugs; Eingabe der Inertial-Daten in ein Bayes'sches Netzwerk zur Bestimmung eines vorausgesagten Ortes des ersten Fahrzeugs und einer vorausgesagten Trajektorie des ersten Fahrzeugs und Aktualisierung des Bayes'schen Netzwerks unter Verwendung des geschätzten aktuellen Ortes und der geschätzten aktuellen Trajektorie des ersten Fahrzeugs unter Verwendung der Odometrie-Daten und der ...

A method for localizing a robot in a localization plane

The invention concerns a method for localizing a robot in a localization plane associated with a bi-dimentional reference with two axis x and y comprising the following steps: determining (200) by odometry an estimation of the coordinates x1 and y1 of the robot as well as an estimation of its orientation Θ1; determining (202) an estimation Θ2 of the orientation of the robot by using a virtual compass; determining (204) an estimation Θ3 of the orientation of the robot by correlating parts of a reference panorama with parts of a query panorama; determining (206) an estimation x4, y4 of the robot position by using an Iterative Closest Points technique; determining the standard deviations σ_x1, σ_x2, σ_θ1 σ_θ2, σ_θ3, σ_x4, σ_y4 of the aforementioned estimations; determining (220) probability distributions G(x1), G(y1), G(Θ1), G(Θ2), G(Θ3), G(x4) and G(y4) of each available estimation using said standard deviations; determining (221) three global distributions GLOB(x), GLOB(y) and GLOB(Θ) and ...

A METHOD FOR LOCALIZING A ROBOT IN A LOCALIZATION PLANE

The invention concerns a method for localizing a robot in a localization plane associated with a bi-dimentional reference with two axis x and y comprising the following steps: determining (200) by odometry an estimation of the coordinates x1 and y1 of the robot as well as an estimation of its orientation T1; determining (202) an estimation T2 of the orientation of the robot by using a virtual compass; determining (204) an estimation T3 of the orientation of the robot by correlating parts of a reference panorama with parts of a query panorama; determining (206) an estimation x4, y4 of the robot position by using an Iterative Closest Points technique; determining the standard deviations s_x1, s_x2, s_?1 s_?2, s_?3, s_x4, s_y4 of the aforementioned estimations; determining (220) probability distributions G(x1), G(y1), G(T1), G(T2), G(T3), G(x4) and G(y4) of each available estimation using said standard deviations; determining (221) three global distributions GLOB(x), GLOB(y) and GLOB(T) and ...

DISPLAY OF SEPARATE COMPUTER VISION BASED POSE AND INERTIAL SENSOR BASED POSE

System und Verfahren zur Steuerung der Bewegung einer Vermessungsvorrichtung

System aus einer Vermessungsvorrichtung zur Bauwerksinspektion und Bauwerkserfassung und einem Tachymeter, wobei die Vermessungsvorrichtung eine schwimmfähige Trägerplattform umfasst, wobei die Trägerplattform mindestens einen Vermessungssensor zur Untersuchung eines wassernahen Bauwerks (28), eine inertiale Messeinheit sowie einen GNSS-Empfänger zum Empfang von GNSS-Signalen von Satelliten eines globalen Navigationssattelitensystems umfasst, wobei das Tachymeter an Land befindlich und auf die Trägerplattform der Vermessungsvorrichtung gerichtet ist, wobei das System weiterhin eine Steuereinheit umfasst, die dazu ausgebildet ist, auf Grundlage von Messdaten der inertialen Messeinheit, auf Grundlage der durch den GNSS-Empfänger empfangenen GNSS-Signale sowie auf Grundlage von durch das Tachymeter erfassten Messdaten eine aktuelle Position der Trägerplattform zu ermitteln und anhand des GNSS-Empfängers die Messdaten der inertialen Messeinheit, die Messdaten des Tachymeters und die GNSS-Signale ...

Object moving system

H:\Interwoven\NRPortb1\DCC\EVK651266 1.docx-24/10/2011 - 67 A system for moving an object within an environment, wherein the system includes at least one modular wheel configured to move the object. The modular wheel includes a body configured to be attached to the object, a wheel, a drive configured to rotate the wheel and a controller configured to control the drive. One or more processing devices configured are provided to receive an image stream including a plurality of captured images from each of a plurality of imaging devices, the plurality of imaging devices being configured to capture images of the object within the environment, analyse the images to determine an object location within the environment, generate control instructions at least in part using the determined object location and provide the control instructions to the controller, the controller being responsive to the control instructions to control the drive and thereby move the object. Fig. 1A ...

LONG TERM IN-FIELD IMU TEMPERATURE CALIBRATION

A method for calibrating a visual-inertial tracking system is described. In one aspect, a method includes measuring a temperature of an inertial measurement unit (IMU) of a visual-inertial tracking system, identifying, from an IMU parametric model of an IMU calibration module, an IMU intrinsic parameter estimate corresponding to the temperature, determining an online IMU intrinsic parameter estimate by operating the visual-inertial tracking system with the IMU intrinsic parameter estimate, providing the online IMU intrinsic parameter estimate to the IMU calibration module, and updating and incorporating the IMU parametric model with the online IMU intrinsic parameter estimate.

СПОСОБ ЛОКАЛИЗАЦИИ РОБОТА В ПЛОСКОСТИ ЛОКАЛИЗАЦИИ

Verfahren zum Erstellen einer Karte, Verfahren zum Ermitteln einer Pose eines Fahrzeugs, Kartierungsvorrichtungen und Lokalisierungsvorrichtungen

Die Erfindung betrifft ein Verfahren zum Erstellen einer Karte eines Navigationsbereichs eines Fahrzeugs, das Verfahren aufweisend:Abfahren einer durch eine im Navigationsbereich vorhandene Spurführungsmarkierung vorgegebenen Bahn mit dem Fahrzeug; Ermitteln von Abständen des Fahrzeugs von gegebenenfalls in einer Umgebung der Bahn vorhandenen Objekten; und Erstellen der Karte basierend auf der Spurführungsmarkierung und den Abständen.Die Erfindung betrifft ferner ein Verfahren zum Ermitteln einer Pose eines Fahrzeugs in einem Navigationsbereich, das Verfahren aufweisend:Ermitteln einer Lage des Fahrzeugs relativ zu einer im Navigationsbereich vorhandenen Spurführungsmarkierung; Ermitteln von Abständen des Fahrzeugs von gegebenenfalls in einer Umgebung des Fahrzeugs vorhandenen Objekten; undErmitteln der Pose basierend auf der Lage, den Abständen und einer Karte, wobei die Karte Positionsinformationen von im Navigationsbereich vorhandenen Objekten und Spurführungsmarkierungen aufweist.Die ...

UNDERWATER OPTICAL POSITIONING SYSTEMS AND METHODS

Systems and methods for positioning objects in underwater environments are provided. The geolocation of a target for an object is determined, and a light source provided as part of a positioning system is operated to project a visible target at that location. The determination of the target location relative to the positioning system can include determining a location of the positioning system using information obtained from a laser system included in the positioning system. The light source used to project the visible target can be the same as a light source included in the laser system. A location of an object relative to the target location can be tracked by the laser system as the object is being moved towards the target location. The described methods and systems utilize one or more non-touch subsea optical systems, including but not limited to laser systems, for underwater infrastructure installation, measurements and monitoring.

Relative inertial measurement system with visual correction

Methods and systems for relative inertial measurement may include a user device comprising an inertial measurement device and/or a camera. A second inertial measurement device may be configured to move with a reference frame. One or more processors may receive inertial measurements from the first and second inertial measurement devices and determine movement of the user device relative to the reference frame by comparing the received inertial measurements. Additionally reference objects in a view of a camera may be used to calibrate the determined motion of the user device within the reference frame.

Pseudo lidar

A navigation system for a host vehicle may include a processor programmed to: receive from a center camera onboard the host vehicle a captured center image including a representation of at least a portion of an environment of the host vehicle, receive from a left surround camera onboard the host vehicle a captured left surround image including a representation of at least a portion of the environment of the host vehicle, and receive from a right surround camera onboard the host vehicle a captured right surround image including a representation of at least a portion of the environment of the host vehicle; provide the center image, the left surround image, and the right surround image to an analysis module configured to generate an output relative to the at least one captured center image; and cause a navigational action by the host vehicle based on the generated output.

PERSONAL NAVIGATION DEVICE OPERABLE IN GNSS-DENIED ENVIRONMENT

A personal navigation device comprising a body, a star tracker, an inclinometer, a clock, a GNSS receiver, and first and second position calculation modules. The first position calculation module is configured to calculate latitude and longitude of the body based on respective outputs from the star tracker, inclinometer, and clock. The second position calculation module is configured to calculate latitude and longitude of the body based on satellite signals received by the GNSS receiver. In one example, the star tracker includes a short-wave infrared camera and the inclinometer includes three accelerometers having non-coplanar axes. The personal navigation device may further include a display device, a display engine, and a user interface configured to enable selection of a particular method of calculating latitude and longitude depending on whether GNSS is available or not.

METHOD, DEVICE, AND COMPUTER PROGRAM FOR DETERMINING THE CHANGE IN POSITION AND/OR ORIENTATION OF THE MOBILE APPARATUS

Provided is a method of determining a change in a position and/or orientation of a mobile apparatus, comprising: acquiring a first data stream indicating a first estimated change in the position and/or orientation of the mobile apparatus in respective ones of a plurality of time frames; acquiring a second data stream indicating a second estimated change in the position and/or orientation of the mobile apparatus in the respective ones of the plurality of time frames, wherein the first data stream has a higher accuracy than the second data stream and the first data stream has a lower robustness than the second data stream; and responsive to a comparison of the first indicated change with the second indicated change in the respective ones of the plurality of time frames, using the first estimated change or the second estimated change to determine the change in the position and/or orientation of the mobile apparatus.

Inertial navigation accuracy enhancement

Drift correction for industrial augmented reality applications

USING OPTICAL SENSORS TO RESOLVE VEHICLE HEADING ISSUES

A control system (100) fuses different sensor data together to determine an orientation of a vehicle (50). The control system (100) receives visual heading data for the vehicle (50) from a camera system (102), global navigation satellite system (GNSS) heading data from a GNSS system (108), and inertial measurement unit (IMU) heading data from an IMU (110). The control system (100) may assign weights to the visual, GNSS, and IMU heading data based on operating conditions of the vehicle (50) that can vary accuracy associated with the different visual, GNSS, and IMU data. The control system (100) then uses the weighted visual, GNSS, and IMU data to determine a more accurate vehicle heading.

복수의 동작 추정기를 이용한 실내 포지셔닝

... 방법 및 시스템은 시간에 걸쳐 모바일 장치의 개별적인 위치 추정치를 형성하기 위해 적어도 두 개의 동작 추정기를 이용한다. 시간에 걸친 위치 추정치는 모바일 장치에서 생성된 센서 데이터를 기반으로 한다. 각각의 동작 추정기는 개별적인 기준 프레임과 연관되고, 각각의 개별적인 위치 추정치는 하나 이상의 추정 성분을 포함한다, 제2 동작 추정기와 연관된 기준 프레임으로부터 제2 동작 추정기와 연관된 기준 프레임으로의 변환이 결정된다. 변환은 제1 및 제2 동작 추정기 각각에 의해 형성된 위치 추정치의 하나 이상의 추정 성분중 적어도 하나의 추정 선분을 적어도 부분적으로 기반하여 결정된다.

INDOOR POSITIONING WITH PLURALITY OF MOTION ESTIMATORS

Methods and systems employ at least two motion estimators to form respective estimates of position of a mobile device over time. The estimates of position over time are based on sensor data generated at the mobile device. Each motion estimator is associated with a respective reference frame, and each respective estimate of position includes one or more estimate components. A transformation from the reference frame associated with a second motion estimator to the reference frame associated with a first motion estimator is determined. The transformation is determined based at least in part on at least one estimate component of the one or more estimate components of the estimates of position formed by each of the first and second motion estimators.

BUNDLE ADJUSTMENT USING EPIPOLAR CONSTRAINTS

Image-augmented inertial navigation system (IAINS) and method

A method for localizing a robot in a localization plane

The invention concerns a method for localizing a robot in a localization plane associated with a bi-dimentional reference with two axis x and y comprising the following steps: determining (200) by odometry an estimation of the coordinates x1 and y1 of the robot as well as an estimation of its orientation Θ1; determining (202) an estimation Θ2 of the orientation of the robot by using a virtual compass; determining (204) an estimation Θ3 of the orientation of the robot by correlating parts of a reference panorama with parts of a query panorama; determining (206) an estimation x4, y4 of the robot position by using an Iterative Closest Points technique; determining the standard deviations σ_x1, σ_x2, σ_θ1 σ_θ2, σ_θ3, σ_x4, σ_y4 of the aforementioned estimations; determining (220) probability distributions G(x1), G(y1), G(Θ1), G(Θ2), G(Θ3), G(x4) and G(y4) of each available estimation using said standard deviations; determining (221) three global distributions GLOB(x), GLOB(y) and GLOB(Θ) and ...

Host vehicle position estimation device

A host vehicle position estimation device includes an observation position estimation unit configured to estimate an observation position of the vehicle based on a result of recognition of the target object performed, a prediction position calculation unit configured to calculate a prediction position of the vehicle from a result of estimation of the host vehicle position in the past based on a result of measurement performed by an internal sensor, a host vehicle position estimation unit configured to estimate the host vehicle position based on the observation position and the prediction position. The host vehicle position estimation unit is configured to give more weighting to the prediction position in the estimation of the host vehicle position such that the host vehicle position is estimated to be close to the prediction position if it is determined that a result of estimation of the host vehicle position is unsteady.

Inertial navigation accuracy enhancement

Inertial navigation accuracy enhancement

UNDERWATER OPTICAL METROLOGY SYSTEM

Described herein are methods and devices for improved location of any and all underwater structures or equipment installed underwater. In particular, systems are disclosed that combine optical and acoustic metrology for locating objects in underwater environments. The systems allow for relative positions of objects to be determined with great accuracy using optical techniques, and support enhanced location of devices that utilize acoustic location techniques. In addition, location information can be provided by the system even in conditions that make optical metrology techniques impossible or impractical.

A METHOD FOR LOCALIZING A ROBOT IN A LOCALIZATION PLANE

The invention concerns a method for localizing a robot in a localization plane associated with a bi-dimentional reference with two axis x and y comprising the following steps: determining (200) by odometry an estimation of the coordinates x1 and y1 of the robot as well as an estimation of its orientation T1; determining (202) an estimation T2 of the orientation of the robot by using a virtual compass; determining (204) an estimation T3 of the orientation of the robot by correlating parts of a reference panorama with parts of a query panorama; determining (206) an estimation x4, y4 of the robot position by using an Iterative Closest Points technique; determining the standard deviations s_x1, s_x2, s_?1 s_?2, s_?3, s_x4, s_y4 of the aforementioned estimations; determining (220) probability distributions G(x1), G(y1), G(T1), G(T2), G(T3), G(x4) and G(y4) of each available estimation using said standard deviations; determining (221) three global distributions GLOB(x), GLOB(y) and GLOB(T) and ...

INDOOR POSITIONING WITH PLURALITY OF MOTION ESTIMATORS

METHOD AND APPARATUS FOR DETERMINING A POSITION OF A VEHICLE

Verfahren zur landmarkenbasierten Lokalisierung eines Fahrzeugs

Die Erfindung betrifft ein Verfahren zur landmarkenbasierten Lokalisierung eines Fahrzeugs (1), wobei in einem Verfahrensabschnitt (VA)- eine Mehrzahl von Positionshypothesen (PH) für eine Fahrzeugposition basierend auf einer Bildung von Assoziationen (A) zwischen sensorisch erfassten Sensor-Landmarkenobjekten (SLM) und in einer digitalen Landkarte hinterlegten Karten-Landmarkenobjekten (KLM) gebildet werden, und- basierend auf einer probabilistischen Filterung der Positionshypothesen (PH) eine wahrscheinlichste Fahrzeugposition als Lokalisierungsergebnis (LE) ermittelt wird und ein garantierter Positionsbereich (PL) ermittelt wird, in dem eine vorgegebene Fehlerobergrenze nicht überschritten wird.Erfindungsgemäß wird dieser Verfahrensabschnitt (VA) mehrfach mit unterschiedlichen Auslegungen der probabilistischen Filterung ausgeführt wird, wobei das Lokalisierungsergebnis (LE1, LE2, LE3) mit dem kleinsten garantierten Positionsbereich (PL1, PL2, PL3) als Fahrzeugposition (eFP) ausgewählt ...

VERFAHREN FÜR HOCHAUFLÖSENDE 3D-BILDGEBUNG

Underwater optical metrology system

Described herein are methods and devices for improved location of any and all underwater structures or equipment installed underwater. In particular, systems are disclosed that combine optical and acoustic metrology for locating objects in underwater environments. The systems allow for relative positions of objects to be determined with great accuracy using optical techniques, and support enhanced location of devices that utilize acoustic location techniques. In addition, location information can be provided by the system even in conditions that make optical metrology techniques impossible or impractical.

Exterior hybrid photo mapping

Embodiments disclosed pertain to the use of user equipment (UE) for the generation of a 3D exterior envelope of a structure based on captured images and a measurement set associated with each captured image. In some embodiments, a sequence of exterior images of a structure is captured and a corresponding measurement set comprising Inertial Measurement Unit (IMU) measurements, wireless measurements (including Global Navigation Satellite (GNSS) measurements) and/or other non-wireless sensor measurements may be obtained concurrently. A closed-loop trajectory of the UE in global coordinates may be determined and a 3D structural envelope of the structure may be obtained based on the closed loop trajectory and feature points in a subset of images selected from the sequence of exterior images of the structure.

Multi-Aircraft Vision and Datalink Based Navigation System and Method

A system and a method of determining an absolute position of a first vehicle can be used in restricted areas. The system performs operations of or the method includes receiving image data from a vision system mounted on a second vehicle, determining a first location of the second vehicle using at least positions of stars in the image data, providing the first location to the first vehicle, determining a first relative position between the first vehicle and the second vehicle using at least one signal communicated between the first vehicle and the second vehicle, and determining the absolute position using at least the relative location data and the first location.

Sensor plausibility using GPS road information

An apparatus including an interface and a processor. The interface may be configured to receive area data and sensor data from a plurality of vehicle sensors. The processor may be configured to extract road characteristics for a location from the area data, predict expected sensor readings at the location for the plurality of sensors based on the road characteristics, calculate dynamic limits for the sensor data in response to the expected sensor readings and determine a plausibility of the sensor data received from the interface when the vehicle reaches the location. The sensor data may be plausible if the sensor data is within the dynamic limits. A confidence level of the sensor data may be adjusted in response to the plausibility of the sensor data.

Method, software product, and system for determining a position and orientation in a 3D reconstruction of the earth's surface

The present disclosure relates to a method for determining a position and an orientation. The method (300) comprises the steps of obtaining (310) sensor data (210) comprising a plurality of images of Earth's surface from at least one calibrated camera; forming (320) a 3D reconstruction (220) of apart of Earth's surface based on obtained sensor data (210); obtaining (330) from a data storage (250), source data (260) indicative of a region comprising at least said part of Earth's surface, wherein said source data (260) comprises a source digital surface model, DSM, (270) for said region, and an orthophoto (280) of said region; determining (340a) a sensor DSM (230) of the 3D reconstruction (220) and a sensor texture (240) of the 3D reconstruction (220) based on the 3D reconstruction (220); matching (350) the sensor DSM (230) and the sensor texture (240) with the source DSM (270) and the orthophoto (280); and determining (360) the position and the orientation of the 3D reconstruction (220) ...

AUTOMATIC, STATIONING OF A GEODETIC SURVEY INSTRUMENT BASED ON REFERENCE MARKER DATABASE

The invention relates to an automatic stationing functionality of a geodetic survey instrument. The survey instrument comprising a targeting unit configured to provide a targeting data measurement, an inertial measurement unit (IMU), an imaging sensor unit configured for providing the functionalities of a visual positioning system (VPS), a communication interface configured to receive a design data comprising position information of reference markers in the environment, and a computing unit. The automatic stationing functionality being configured for calculating a coarse pose of the instrument based on the IMU and/or the VPS pose data, selecting a plurality of reference markers to be targeted based on the coarse pose and the design data, and determining a fine pose of the instrument based on the targeting data measurement of the plurality reference markers.

INFORMATIONSVERARBEITUNGSVORRICHTUNG, INFORMATIONSVERARBEITUNGSVERFAHREN, PROGRAMM UND BEWEGLICHER KÖRPER

Die Informationsverarbeitungsvorrichtung gemäß einem Aspekt der vorliegenden Technologie weist eine Abschätzungseinheit, eine Generierungseinheit und eine Frequenzsteuerungseinheit auf. Die Abschätzungseinheit schätzt mindestens eine von einer Position oder einer Stellung eines mobilen Gegenstands ab. Die Generierungseinheit generiert einen Bewegungsplan zum Bewegen des mobilen Gegenstands. Die Frequenzsteuerungseinheit steuert eine Aktualisierungsfrequenz des Bewegungsplans, die von der Generierungseinheit durchzuführen ist, auf Grundlage von Lastindexinformationen, die als ein Index einer Belastung der Abschätzungseinheit dienen.

A method and system for combining sensor data

The evolution of a metric of interest over time is determined using sensor data from which position or movement may be inferred. First and second data are obtained within two respective time periods (701, 702), and the evolution of the metric is determined between two time instances (709), at least one of which is within the aforementioned time periods, using constraints relating to at least one of the first and second data and a motion model of a platform to which the sensor is mounted. The second data may involve a second sensor mounted to a second platform. The reliability of each sensor data may be assessed by analysing the data over part of its respective time period, and used to adjust the duration of overlap of the two time periods. The motion model may depend on a parameter (706, 708) such as a pedestrian’s leg length, speed or height.

Drift correction for industrial augmented reality applications

This application concerns a method for facilitating creation of a map of a real-world, process control environment, the method comprising: tracking locations of the mobile device as the user moves through the mapped environment, capturing, by a camera of the mobile device, images of the mapped environment as the user moves through the mapped environment, receiving an indication that the user intends to add a node to the map, providing one or more images of the captured images to a machine leaming (ML) model, the ML model being trained to process images to recognize object types, predicting, by the ML model processing the one or more images, an object type corresponding to a specific object within a field of view of the camera and causing a display of the mobile device to superimpose, on a real-world view presented to the user, an indication of the predicted object type to facilitate user designation of a descriptor for the new node.

aprendizado específico de usuário para modelagem de movimento de pedestre melhorada em um dispositivo móvel

MONOCULAR VISUAL-INERTIAL ALIGNMENT FOR SCALED DISTANCE ESTIMATION ON MOBILE DEVICES

Methods, techniques, apparatus, and algorithms are described for robustly measuring real-world distances using any mobile device equipped with an accelerometer and monocular camera. A general software implementation processes 2D video, precisely tracking points of interest across frames to estimate the unsealed trajectory of the device, which is used to correct the device's inertially derived trajectory. The visual and inertial trajectories are then aligned in scale space to estimate the physical distance travelled by the device and the true distance between the visually tracked points.

A method and system for combining sensor data

A Sensor Device for Vehicles

The present invention is a sensor device for vehicles. The system has an electronic navigation sensor, a multi-spectral data sensor, a router for receiving data from each sensor, a communications device connected to the router for communicating data and a computer processor. The computer processor is used to receive data from the sensors, store real time data from the sensors, and store a master data sequence file of data previously collected from the same operating track. The sensor device has software on the computer processor which is programmed to correlate data from the sensors with data from a master data sequence file for the given track, make inferences based on data about an event, and communicate alarms as programmed. Fgr Figure 1 ...

METHOD AND DEVICE FOR PROVIDING GUIDANCE TO STREET VIEW DESTINATION

Disclosed is a method and device for providing guidance to a street view destination. The method includes: acquiring a real scenario image of a scenario in which a device is located; determining, according to a current location and a device facing direction of the device, annotated information needing to be displayed; displaying, in the real scenario image, the annotated information needing to be displayed; determining selected annotated information; and displaying detailed information of a street view corresponding to the selected annotated information.

Efficient vision-aided inertial navigation using a rolling-shutter camera

Vision-aided inertial navigation techniques are described. In one example, a vision-aided inertial navigation system (VINS) comprises an image source to produce image data at a first set of time instances along a trajectory within a three-dimensional (3D) environment, wherein the image data captures features within the 3D environment at each of the first time instances. An inertial measurement unit (IMU) to produce IMU data for the VINS along the trajectory at a second set of time instances that is misaligned with the first set of time instances, wherein the IMU data indicates a motion of the VINS along the trajectory. A processing unit comprising an estimator that processes the IMU data and the image data to compute state estimates for 3D poses of the IMU at each of the first set of time instances and 3D poses of the image source at each of the second set of time instances along the trajectory. The estimator computes each of the poses for the image source as a linear interpolation from ...

METHOD FOR ALIGNING CROWD-SOURCED DATA TO PROVIDE AN ENVIRONMENTAL DATA MODEL OF A SCENE

Method and device for providing guidance to street view destination

Disclosed is a method and device for providing guidance to a street view destination. The method includes: acquiring a real scenario image of a scenario in which a device is located; determining, according to a current location and a device facing direction of the device, annotated information needing to be displayed; displaying, in the real scenario image, the annotated information needing to be displayed; determining selected annotated information; and displaying detailed information of a street view corresponding to the selected annotated information.

MAP ESTABLISHMENT METHOD AND MAP ESTABLISHMENT SYSTEM

A map establishment method and a map establishment system are provided. The map establishment method includes: detecting a physical motion performed by a user and generating motion sensing data by at least one motion sensor; obtaining spatial dimension information, in multiple directions, of a target place where the user is located and information of an obstacle in the target place by a deep learning model according to the motion sensing data; and generating map data according to the spatial dimension information and the information of the obstacle, wherein the map data reflects a contour of the target place where the user is located and a distribution status of at least one obstacle in the target place.

System and method for generating precise road lane map data

An in-vehicle system for generating precise, lane-level road map data includes a GPS receiver operative to acquire positional information associated with a track along a road path. An inertial sensor provides time local measurement of acceleration and turn rate along the track, and a camera acquires image data of the road path along the track. A processor is operative to receive the local measurement from the inertial sensor and image data from the camera over time in conjunction with multiple tracks along the road path, and improve the accuracy of the GPS receiver through curve fitting. One or all of the GPS receiver, inertial sensor and camera are disposed in a smartphone. The road map data may be uploaded to a central data repository for post processing when the vehicle passes through a WiFi cloud to generate the precise road map data, which may include data collected from multiple drivers.

6DoF positioning tracking device and method, and electronic apparatus

A six degrees of freedom (6 DoF) positioning tracking device and method, and an electronic apparatus are provided. The device includes at least three tracking cameras, an inertial navigation unit and a computation processing unit, where the at least three tracking cameras are distributed at preset angles and are configured to obtain image data in a current environment and transmit the image data to the computation processing unit; the inertial navigation unit is configured to obtain state information of the 6 DoF positioning tracking device in the current environment and transmit the state information to the computation processing unit; and the computation processing unit is configured to determine 6 DoF data of the 6 DoF positioning tracking device relative to the current environment according to the image data and the state information.

Sensor perturbation

Perception sensors of a vehicle can be used for various operating functions of the vehicle. A computing device may receive sensor data from the perception sensors, and may calibrate the perception sensors using the sensor data, to enable effective operation of the vehicle. To calibrate the sensors, the computing device may project the sensor data into a voxel space, and determine a voxel score comprising an occupancy score and a residual value for each voxel. The computing device may then adjust an estimated position and/or orientation of the sensors, and associated sensor data, from at least one perception sensor to minimize the voxel score. The computing device may calibrate the sensor using the adjustments corresponding to the minimized voxel score. Additionally, the computing device may be configured to calculate an error in a position associated with the vehicle by calibrating data corresponding to a same point captured at different times.

Arbeitsmaschine

Eine Arbeitsmaschine (1) ist mit einem Arbeitsgerät (12), einem Drehkörper (13), an dem das Arbeitsgerät befestigt ist, einem Topographiesensor (35) zum Vermessen einer Topographie und einer Steuereinrichtung (27) versehen. Die Steuereinrichtung (27) bestimmt einen Aushubstartpunkt (S1) für das Arbeitsgerät (12) anhand von Topographiedaten, die die von dem Topographiesensor (35) vermessene Topographie angeben, und bewirkt, dass sich das Arbeitsgerät (12) von einer aktuellen Position (S2) des Arbeitsgeräts (12) zu dem Aushubstartpunkt (S1) bewegt.

SYSTEM UND VERFAHREN ZUR VERBESSERUNG EINES NICHT INERTIALEN TRACKING-SYSTEMS MIT INERTIALEN BESCHRÄNKUNGEN

Ein System und ein Verfahren zum Erzeugen eines Tracking-Zustands für eine Vorrichtung beinhaltet Synchronisieren von Messdaten von exterozeptiven Sensoren und einer inertialen Messeinheit (IMU). Eine Verarbeitungseinheit ist programmiert, eines der Messsignale um einen Zeitversatz zu versetzen, der einen Gesamtfehler zwischen einer Rotationsänderung der Vorrichtung, die durch die exterozeptiven Sensordaten über ein durch eine Abtastrate des exterozeptiven Sensors definiertes Zeitintervall vorhergesagt wird, und einer Rotationsänderung der Vorrichtung, die durch die IMU-Sensordaten über das Zeitintervall vorhergesagt wird, minimiert.

A sensor device for vehicles

A sensor device 10 for mounting on a vehicle (e.g. train 12,Fig.1) has an encasement 14 containing electronic navigation sensors (e.g. GPS, INS 32, 34); a multi-spectral data sensor (e.g. a sensor array comprising RGB cameras 16, 24, LIDAR detector 18, telephoto lens camera 20 and infra-red camera 22); a router for receiving data from each sensor; a communications device connected to the router; and a computer processor. The processor correlates data from the sensors with data from a master data sequence file (MDSF) to make inferences about an event and communicate alarms. The MDSF may comprise artifacts extracted from previous runs, sorted as a sequence of objects, events and conditions. The encasement may have a visor hood for protection from solar radiation and an outwardly facing, sloping glass panel 26 with a gallium arsenide insert 28 allowing infra-red light to penetrate to the IR camera 22. The encasement may detect if the sensor device has been opened.

Location tracking device and method using feature matching

This application relates to a location tracking device and method using a feature matching. The location tracking device may include a sensor, a camera, and a controller. The sensor is provided in a predetermined object and collects sensing information including at least one of speed, direction, gravity, and acceleration of the object. The camera is provided in the predetermined object and collects image information by capturing an image. The controller calculates an initial fundamental matrix (F0) by using the collected sensing information and calibration information of the camera, detects feature points of the image information, performs a feature matching in a fundamental matrix (F) by combining the initial fundamental matrix and the feature points, and tracks a location of the object by using a result of the feature matching.

SYSTEM AND METHOD FOR GENERATING PRECISE ROAD LANE MAP DATA

An in-vehicle system for generating precise, lane-level road map data includes a GPS receiver operative to acquire positional information associated with a track along a road path. An inertial sensor provides time local measurement of acceleration and turn rate along the track, and a camera acquires image data of the road path along the track. A processor is operative to receive the local measurement from the inertial sensor and image data from the camera over time in conjunction with multiple tracks along the road path, and improve the accuracy of the GPS receiver through curve fitting. One or all of the GPS receiver, inertial sensor and camera are disposed in a smartphone. The road map data may be uploaded to a central data repository for post processing when the vehicle passes through a WiFi cloud to generate the precise road map data, which may include data collected from multiple drivers.

METHOD AND SYSTEM FOR OPTICAL-INERTIAL TRACKING MOVABLE OBJECTS

Image-Augmented Inertial Navigation System (Iains) and Method

An image-augmented inertial navigation system (LAWS) mounted on a vehicle ( 10 ) includes an inertial navigation system (INS) configured to estimate a navigation state vector and an imager ( 12 ) configured to output pixel signals associated with terrain features passing through a field of view (x, y, z) of the imager. The system (IAINS) further includes a processing unit operatively connected to the inertial navigation system (INS) and the imager ( 12 ). The processing unit is configured to sense a distance from the imager to a centroid of one or more of the terrain features passing though a field of view of the imager for a given image frame associated with the feature pixel signals. The processing unit is also configured to track each terrain feature as the terrain features pass through the field of view of the imager. The processing unit is further configured to update the navigation state vector of the inertial navigation system (INS) based on calculated NED (North, East, Down) coordinates ...

SCENE INTELLIGENCE FOR COLLABORATIVE SEMANTIC MAPPING WITH MOBILE ROBOTS

Various aspects of techniques, systems, and use cases include provide instructions for operating an autonomous mobile robot (AMR). A technique may include capturing audio or video data using a sensor of the AMR, performing a classification of the audio or video data using a trained classifier, and identifying a coordinate of an environmental map corresponding to a location of the audio or video data. The technique may include updating the environmental map to include the classification as metadata corresponding to the coordinate. The technique may include communicating the updated environmental map to an edge device.

VEHICLE POSITIONING SYSTEM AND METHOD, AND VEHICLE

Image-augmented inertial navigation system (IAINS) and method

Marine equipment inventory tool

A system and method for tracking marine equipment is provided. Generally, the system and method of the present disclosure are designed to generate indicia corresponding to the inventory level of marine equipment used for a particular marine activity. To facilitate the assignment of indicia reflecting the inventory level of marine equipment used for a marine activity, the system and method of the present disclosure uses a plurality of equipment profiles having a defined lower limit and quantity associated with each piece of marine equipment. The lower limit may be manually input or automatically generated. The quantity may be tracked by the system using equipment transmitters and equipment sensors. In a preferred embodiment, the indicia indicate whether the quantity of a piece of marine equipment has fallen below a certain specified level as defined by the user. Users may purchase new marine equipment from third-party retailers via the user interface.

A METHOD, SOFTWARE PRODUCT, AND SYSTEM FOR DETERMINING A POSITION AND ORIENTATION IN A 3D RECONSTRUCTION OF THE EARTH'S SURFACE

The present disclosure relates to a method for determining a position and an orientation. The method (300) comprises the steps of obtaining (310) sensor data (210) comprising a plurality of images of Earth's surface from at least one calibrated camera; forming (320) a 3D reconstruction (220) of a part of Earth's surface based on obtained sensor data (210); obtaining (330) from a data storage (250), source data (260) indicative of a region comprising at least said part of Earth's surface, wherein said source data (260) comprises a source digital surface model, DSM, (270) for said region, and an orthophoto (280) of said region; determining (340a) a sensor DSM (230) of the 3D reconstruction (220) and a sensor texture (240) of the 3D reconstruction (220) based on the 3D reconstruction (220); matching (350) the sensor DSM (230) and the sensor texture (240) with the source DSM (270) and the orthophoto (280); and determining (360) the position and the orientation of the 3D reconstruction (220) ...

Vorrichtung und Verfahren zum Schätzen einer Position in einem automatisierten Parkdienstsystem

Eine Vorrichtung zum Schätzen einer Position in einem automatisierten Parkdienstsystem weist auf: einen Frontkameraprozessor, der zum Verarbeiten eines Frontbildes eines Fahrzeugs ausgebildet ist; einen Rundumsichtmonitor-Prozessor (SVM-Prozessor), der dazu ausgebildet ist, eine Kurzstreckenfahrspur bzw. -fahrspurbegrenzung und eine Haltelinie durch Verarbeiten eines Rundumsichtbildes des Fahrzeugs zu erkennen; eine Kartendateneinheit, die dazu ausgebildet ist, eine hochauflösende Karte zu speichern; und eine Steuerung, die dazu ausgebildet ist, eine Karte, die einen als Parkzone ausgewiesenen Bereich aufweist, von der Kartendateneinheit herunterzuladen, wenn das Einfahren des Fahrzeugs in einen Parkplatz erkannt wird, und einen Positionsmesswert des Fahrzeugs zu korrigieren, indem ein Kartenabgleich auf der Basis der Erkennungs- und Verarbeitungsergebnisse des Frontkameraprozessors und des SVM-Prozessors und der Parkplatzkarte der Kartendateneinheit durchgeführt wird, wenn eine Startposition ...

A METHOD FOR LOCALIZING A ROBOT IN A LOCALIZATION PLANE

LANE LINE POSITIONING METHOD AND APPARATUS, AND STORAGE MEDIUM THEREOF

This disclosure is directed to a lane line positioning method and apparatus. The method includes obtaining inertial information, target traveling information, and first position information of a vehicle. The inertial information comprises information measured by an inertial measurement unit of the vehicle. The target traveling information comprises traveling information of the vehicle acquired at a first moment. The first position information comprises a position of the vehicle at the first moment. The method includes determining second position information according to the target traveling information and the first position information and determining third position information of the vehicle at a second moment based on the inertial information of the vehicle and the second position information. The method includes determining a position of a lane line in a map according to the third position information and relative position information. 1. A method for positioning a lane line , comprising:obtaining inertial information, target traveling information, and first position information of a vehicle, the inertial information comprising information measured by an inertial measurement unit of the vehicle, the target traveling information comprising traveling information of the vehicle acquired at a first moment, and the first position information comprising a position of the vehicle at the first moment;determining second position information according to the target traveling information and the first position information;determining third position information of the vehicle at a second moment based on the inertial information of the vehicle and the second position information, the second moment being later than the first moment; anddetermining a position of a lane line in a map according to the third position information and relative position information, the relative position information indicating a relative position between a detected lane line and the vehicle.2. The ...

Inertia-based navigation apparatus and inertia-based navigation method based on relative preintegration

An inertia-based navigation apparatus and an inertia-based navigation method based on relative preintegration are provided. The inertia-based navigation apparatus includes: a first sensor detecting and outputting motion information about a moving body which is moving, based on a first coordinate system; a second sensor detecting and outputting inertia data about a translational acceleration and a rotational angular velocity related to the movement of the moving body, based on a second coordinate system; and a controller determining, at every first time, pose information about a position, a velocity and an attitude of the moving body in a reference coordinate system, based on the motion information and the inertia data.

Processing of multispectral sensors for autonomous flight

A system and method are disclosed for design of a suite of multispectral (MS) sensors and processing of enhanced data streams produced by the sensors for autonomous aircraft flight. The suite of MS sensors is specifically configured to produce data streams for processing by an autonomous aircraft object identification and positioning system processor. Multiple, diverse MS sensors image naturally occurring, or artificial features (towers buildings etc.) and produce data streams containing details which are routinely processed by the object identification and positioning system yet would be unrecognizable to a human pilot. The object identification and positioning system correlates MS sensor output with a-priori information stored onboard to determine position and trajectory of the autonomous aircraft. Once position and trajectory are known, the object identification and positioning system sends the data to the autonomous aircraft flight management system for autopilot control of the autonomous ...

NAVIGATION IN BUILDINGS WITH RECTANGULAR FLOOR PLAN

An apparatus and method for providing a direction based on an angle of a reference wall is provided. A mobile device uses an angle of a horizontal feature from an image to calibrate a sensor and future sensor measurements. The angle of the horizontal feature is determined by image processing and this angle is mapped to one of four assumed parallel or perpendicular angles of an interior of a building. A sensor correction value is determined from a difference between the sensor-determined angle and the image-processing determined angle. The image processing determined angle is assumed to be very accurate and without accumulated errors or offsets that the sensor measurements may contain.

AUGMENTATION OF GLOBAL NAVIGATION SATELLITE SYSTEM BASED DATA

A vehicle computing system validates location data received from a Global Navigation Satellite System receiver with other sensor data. In one embodiment, the system calculates velocities with the location data and the other sensor data. The system generates a probabilistic model for velocity with a velocity calculated with location data and variance associated with the location data. The system determines a confidence score by applying the probabilistic model to one or more of the velocities calculated with other sensor data. In another embodiment, the system implements a machine learning model that considers features extracted from the sensor data. The system generates a feature vector for the location data and determines a confidence score for the location data by applying the machine learning model to the feature vector. Based on the confidence score, the system can validate the location data. The validated location data is useful for navigation and map updates.

sistema de controle para juntar dados de diferentes sensores e determinar uma orientação de um veículo e programa de computador para calcular uma direção de um veículo

NAVIGATION IN BUILDINGS WITH RECTANGULAR FLOOR PLAN

An apparatus and method for providing a direction based on an angle of a reference wall is provided. A mobile device uses an angle of a horizontal feature from an image to calibrate a sensor and future sensor measurements. The angle of the horizontal feature is determined by image processing and this angle is mapped to one of four assumed parallel or perpendicular angles of an interior of a building. A sensor correction value is determined from a difference between the sensor-determined angle and the image-processing determined angle. The image processing determined angle is assumed to be very accurate and without accumulated errors or offsets that the sensor measurements may contain.

ERROR CORRECTION OF AIRBORNE VEHICLES USING NATURAL PATTERNS

ELECTRONIC DEVICE FOR GENERATING MAP DATA AND OPERATION METHOD THEREOF

Provided are an electronic device for generating map data and an operating method of the electronic device. The operating method of the electronic device includes: obtaining image data of a first resolution and image data of a second resolution for each of a plurality of nodes generated while the electronic device moves; obtaining location information with respect to each of the generated nodes, by using the image data of the second resolution; generating and storing map data by matching the obtained location information with the image data of the first resolution for each node; and estimating a current location of the electronic device by using the generated map data and the image data of the first resolution.

Location-estimating device and computer program for location estimation

A location-estimating device comprises a processor configured to acquire first locational information representing the location of a moving object for each first information acquisition time and calculate a first estimated location, acquire second locational information representing the location of the moving object for each second information acquisition time and calculate a second estimated location, and when the first estimated location has been determined, calculate the first movement amount and moving direction between the first information acquisition time and current time, and estimate the location at the current time based on the first estimated location, first movement amount and moving direction, or when the first estimated location is not determined, calculate a second movement amount and moving direction between the preceding second information acquisition time and current time, and estimate the location at the current time based on the second estimated location, second movement ...

Fault-tolerance to provide robust tracking for autonomous and non-autonomous positional awareness

The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Verfahren und mobile Erfassungsvorrichtung zur Erfassung von Infrastrukturelementen eines unterirdischen Leitungsnetzwerks

Die Erfindung betrifft ein Verfahren und eine Vorrichtung zur Erfassung von freiliegenden Infrastrukturelementen eines unterirdischen Leitungsnetzwerks, insbesondere in einer geöffneten Baugrube, mit einer mobilen Erfassungsvorrichtung (1).

Positioning apparatus, recording medium, and positioning method

A positioning apparatus according to the present invention includes: a detector configured to detect that a movable object has moved from a first position to a second position; a data acquisition unit configured to acquire first position data, second position data, and virtual moving direction data indicating a moving direction of the movable object having moved from the first position to the second position in a virtual space; and a correction unit configured to correct the virtual moving direction data so that the moving direction of the movable object in the virtual space follows a first direction connecting the first position and the second position by using the first position data and the second position data. Therefore, deterioration of positioning accuracy of the movable object in the virtual space can be prevented.

System and method for enhancing non-inertial tracking system with inertial constraints

A system and method for generating a tracking state for a device includes synchronizing measurement data from exteroceptive sensors and an inertial measurement unit (IMU). A processing unit is programmed to offset one of the measurement signals by a time offset that minimizes a total error between a change in rotation of the device predicted by the exteroceptive sensor data over a time interval defined by an exteroceptive sensor sampling rate and a change in rotation of the device predicted by the IMU sensor data over the time interval.

DRIFT CALIBRATION METHOD AND DEVICE FOR INERTIAL MEASUREMENT UNIT, AND UNMANNED AERIAL VEHICLE

Method and device for drift calibration of an inertial measurement unit, and an unmanned aerial vehicle are provided. The drift calibration method includes obtaining video data captured by a photographing device; and determining a measurement error of the inertial measurement unit according to the video data and rotation information of the inertial measurement unit when the photographing device capturing the video data. The rotation information of the inertial measurement unit includes the measurement error of the inertial measurement unit.

Method and apparatus for high resolution 3D imaging

A system and method for imaging a three-dimensional scene having one or more objects. The system includes a light source, a detector array, a timing circuit, an inertial guidance system and a processor connected to the timing circuit and the inertial guidance system. The light source generates an optical pulse and projects the optical pulse on an object so that it is reflected as a reflected pulse. The detector array includes a plurality of detectors, wherein the detectors are oriented to receive the reflected pulse. The timing circuit determines when the reflected pulse reached detectors on the detector array. The inertial guidance system measures angular velocity and acceleration. The processor forms a composite image of the three-dimensional scene as a function of camera position and range to objects in the three-dimensional scene.

Mobile system and method of scanning an environment

A system and method for measuring three-dimensional (3D) coordinate values of an environment is provided. The system includes a movable base unit a first scanner and a second scanner. One or more processors performing a method that includes causing the first scanner to determine first plurality of coordinate values in a first frame of reference based on an emitted first beam of light and a received first reflected light. The second scanner determines a second plurality of 3D coordinate values in a second frame of reference as the base unit is moved from a first position to a second position. The determining of the first coordinate values and the second plurality of 3D coordinate values being performed simultaneously. The second plurality of 3D coordinate values are registered in a common frame of reference based on the first plurality of coordinate values.

IMAGE-BASED TECHNIQUES FOR STABILIZING POSITIONING ESTIMATES

A device implementing a system for estimating device location includes at least one processor configured to receive a first estimated position of the device at a first time. The at least one processor is further configured to capture, using an image sensor of the device, images during a time period defined by the first time and a second time, and determine, based on the images, a second estimated position of the device, the second estimated position being relative to the first estimated position. The at least one processor is further configured to receive a third estimated position of the device at the second time, and estimate a location of the device based on the second estimated position and the third estimated position.

Methods for geospatial positioning and portable positioning devices thereof

Embodiments provide for a method of determining a geospatial position of a point of interest and a portable positioning device. In one embodiment, the method includes collecting data from a receiving unit and data from at least one of an imaging device and an IMU of the positioning device for each one of a plurality of positions of the positioning device. The collected data is then transmitted to a data fusing processor for determining orientations and positions of the positioning device for the plurality of positions in a global coordinate system. Further, the method includes obtaining a pointing input including a sighting direction towards the point of interest from the positioning device being positioned at at least one reference position. The pointing input is transmitted to the data fusing processor for identifying the point of interest and for determining the geospatial position of the point of interest in the global coordinate system.

Systems and methods for landmark selection for navigation

Systems and methods are provided for selecting landmarks for navigation. In one embodiment, a system comprises an IMU that provides inertial measurements for a vehicle and at least one image sensor that acquires measurements of the vehicle's environment. The system also comprises a processing unit that calculates a navigation solution for the vehicle based on the inertial measurements, identifies a plurality of landmarks in the acquired measurements, and identifies a plurality of usable landmarks from the plurality of landmarks. The processing unit also selects a subset of useable landmarks from the plurality of useable landmarks such that the subset of landmarks has a smaller dilution of precision (DOP) than other possible subsets of landmarks from the plurality of useable landmarks, and calculates an updated navigation solution from the subset of landmarks. The DOP is an amplification factor of measurement errors derived from the geometry of the subset of useable landmarks.

Integrated photogrammetric light communications positioning and inertial navigation system positioning

A mobile device includes an inertial navigation system (INS) to measure inertial quantities associated with movement of the device, and estimate a kinematic state associated with the movement based on the measured inertial quantities. The device includes a light receiver to record light beams originating from lights at respective image positions in a sequence of images. The device photogrammetrically determines its position relative to the originating lights based on predetermined real-world positions and corresponding image positions of the lights. The device corrects the estimated kinematic state based on the photogrammetrically determined position, to produce a corrected estimated kinematic state.

Laser scanner with real-time, online ego-motion estimation

A mapping system, comprising an inertial measurement unit; a camera unit; a laser scanning unit; and a computing system in communication with the inertial measurement unit, the camera unit, and the laser scanning unit, wherein the computing system computes first measurement predictions based on inertial measurement data from the inertial measurement unit at a first frequency, second measurement predictions based on the first measurement predictions and visual measurement data from the camera unit at a second frequency and third measurement predictions based on the second measurement predictions and laser ranging data from the laser scanning unit at a third frequency.

Techniques for Accurate Pose Estimation

The described technology regards an augmented reality system and method for estimating a position of a location of interest relative to the position and orientation of a display based upon a retroactive adjustment of a previously rendered position and orientation of the display, by means of an adjust-update-predict (AUP) cycle, and calculating the location of interest relative to the position and orientation of the display. Systems of the described technology include including a plurality of sensors, a processing module or other computation means, and a database. Methods of the described technology use data from the sensor package useful to accurately render graphical user interface information on a display.

Crowd sourcing data for autonomous vehicle navigation

A method of processing vehicle navigation information for use in autonomous vehicle navigation is provided. The method includes receiving, by a server, navigation information from a plurality of vehicles. The navigation information from the plurality of vehicles is associated with a common road segment. The method also includes storing, by the server, the navigation information associated with the common road segment. The method also includes generating, by the server, at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information from the plurality of vehicles. The method further includes distributing, by the server, the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating the one or more autonomous vehicles along the common road segment.

Systems and methods for identifying landmarks

A system for identifying a landmark for use in autonomous vehicle navigation is provided. The system includes at least one processor programmed to receive at least one identifier associated with the landmark; associate the landmark with a corresponding road segment; update an autonomous vehicle road navigation model relative to the corresponding road segment to include the at least one identifier associated with the landmark; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles. The at least one identifier is determined based on acquisition, from a camera associated with a host vehicle, of at least one image representative of an environment of the host vehicle; analysis of the at least one image to identify the landmark in the environment of the host vehicle; and analysis of the at least one image to determine the at least one identifier associated with the landmark.

Autonomous vehicle tail alignment navigation

A system for navigating an autonomous vehicle along a road segment is disclosed. The system may have at least one processor. The processor may be programmed to receive from an image capture device, images representative of an environment of the autonomous vehicle. The processor may also be programmed to determine a travelled trajectory along the road segment based on analysis of the images. Further, the processor may be programmed to determine a current location of the autonomous vehicle along a predetermined road model trajectory based on analysis of one or more of the plurality of images. The processor may also be programmed to determine a heading direction based on the determined traveled trajectory. In addition, the processor may be programmed to determine a steering direction, relative to the heading direction, by comparing the traveled trajectory to the predetermined road model trajectory at the current location of the autonomous vehicle.

Sparse map for autonomous vehicle navigation

A non-transitory computer-readable medium is provided. The computer-readable medium includes a sparse map for autonomous vehicle navigation along a road segment. The sparse map includes a polynomial representation of a target trajectory for the autonomous vehicle along the road segment, and a plurality of predetermined landmarks associated with the road segment. The plurality of predetermined landmarks are spaced apart by at least 50 meters, and the sparse map has a data density of no more than 1 megabyte per kilometer.

Self-aware system for adaptive navigation

Systems and methods are provided for self-aware adaptive navigation. In one implementation, a navigation system for a vehicle may include at least one processor. The at least one processor may be programmed to determine a navigational maneuver for the vehicle based, at least in part, on a comparison of a motion of the vehicle with respect to a predetermined model representative of a road segment. The at least one processor may be further programmed to receive, from a camera, at least one image representative of an environment of the vehicle. The at least one processor may be further programmed to determine, based on analysis of the at least one image, an existence in the environment of the vehicle of an navigational adjustment condition, cause the vehicle to adjust the navigational maneuver based on the existence of the navigational adjustment condition, and store information relating to the navigational adjustment condition.

Gnss and optical guidance and machine control

A global navigation satellite sensor system (GNSS) and gyroscope control system for vehicle steering control comprising a GNSS receiver and antennas at a fixed spacing to determine a vehicle position, velocity and at least one of a heading angle, a pitch angle and a roll angle based on carrier phase position differences. The system also includes a control system configured to receive the vehicle position, heading, and at least one of roll and pitch, and configured to generate a steering command to a vehicle steering system. The system includes gyroscopes for determining system attitude change with respect to multiple axes for integrating with GNSS-derived positioning information to determine vehicle position, velocity, rate-of-turn, attitude and other operating characteristics. Relative orientations and attitudes between motive and working components can be determined using optical sensors and cameras. The system can also be used to guide multiple vehicles in relation to each other.

Uav navigation and sensor system configuration

Systems, methods and devices for use with unmanned aerial vehicles (UAV). A central controller is coupled to the autopilot system for a UAV. Navigation is implemented by using two GPS antennas and obtaining a difference between the locations from these two antenna to arrive at a high precision bearing or direction of travel. This single GPS derived bearing is used to trigger all the various subsystems on the UAV for imaging or mapping. Areas and locations to be mapped and imaged are determined by geolocation and mapping and imaging equipment are triggered based on the single GPS signal derived from the two GPS antennas. To reduce vibration effects on navigational and imaging or mapping equipment, these are positioned as close as possible to the vehicle's center of gravity and are deployed in a shielded box on vibration isolation mounts.

Adaptive road model manager

Systems and methods are provided for interacting with a plurality of autonomous vehicles. In one implementation, a system may include at least one processor. The at least one processor may be programmed to receive from each of the plurality of autonomous vehicles navigational situation information associated with an occurrence of an adjustment to a determined navigational maneuver, analyze the navigational situation information, determine, based on the analysis of the navigational situation information, whether the adjustment to the determined navigational maneuver was due to a transient condition, and update the predetermined model representative of the at least one road segment if the adjustment to the determined navigational maneuver was not due to a transient condition.

Navigating an unmanned aerial vehicle

Systems and methods for navigating an unmanned aerial vehicle are provided. One example aspect of the present disclosure is directed to a method for navigating an unmanned aerial vehicle. The method includes capturing, by one or more processors associated with a flight management system of an unmanned aerial vehicle, one or more images. The method includes assessing, by the one or more processors, signals from an inertial measurement unit (IMU). The method includes processing, by the one or more processors, the one or more captured images based on the assessed signals to generate one or more corrected images. The method includes processing, by the one or more processors, the one or more generated corrected images to approximate position data. The method includes causing, by the one or more processors, the unmanned aerial vehicle to be controlled based on the position data.

Data generation method for generating and updating a topological map for at least one room of at least one building

The present disclosure invention relates to a data generation method for generating and updating at least one room in at least one building in the surroundings of a vehicle, by at least one vehicle, in which an assessment of characteristic motion is corrected without GPS reception by means of subsequently available GPS data, and used for at least one topological map for at least one room of at least one building.

GIMBAL POSE CORRECTION METHOD AND DEVICE

A gimbal pose correction method includes obtaining a first pose of a gimbal based on an Inertial Measurement Unit (IMU) arranged at a vertical compensation device configured to be coupled to the gimbal and compensate for movement of the gimbal in a vertical direction, obtaining a second pose of the vertical compensation device based on a vision device arranged at the vertical compensation device, and correcting the first pose according to the second pose. 1. A gimbal pose correction method comprising:obtaining a first pose of a gimbal based on an Inertial Measurement Unit (IMU) arranged at a vertical compensation device, the vertical compensation device being configured to be coupled to the gimbal and compensate for movement of the gimbal in a vertical direction;obtaining a second pose of the vertical compensation device based on a vision device arranged at the vertical compensation device; andcorrecting the first pose according to the second pose.2. The method of claim 1 , wherein:the vertical compensation device includes a main body and an axis arm configured to be connected to the gimbal;the IMU is arranged at the axis arm; andthe vision device is arranged at the main body.3. The method of claim 1 , wherein:the vision device includes a visual odometer; andthe second pose includes a velocity and a position of the vertical compensation device.4. The method of claim 3 , the vertical compensation device includes an axis arm configured to be connected to the gimbal and compensate for the movement of the gimbal in the vertical direction via rotation; and', 'an angular velocity sensor is arranged at the axis arm;, 'wherein 'obtaining a joint angle of the axis arm based on the angular velocity sensor.', 'the method further comprising, before obtaining the second pose5. The method of claim 4 , wherein: 'obtaining the second pose includes performing coordinate conversion on a reference velocity of the vertical compensation device output by the vision device according to ...

VISION-BASED NAVIGATION SYSTEM

A method for integrating a vision-based navigation system into an aircraft navigation algorithm includes the step of obtaining a previous aircraft location as a latitude-longitude grid coordinate; implementing vision odometry based location determination with several steps. The method includes the step of using one or more digital cameras to obtain a set of digital images of the landscape beneath the aircraft, identifying a set of key points in the landscape using a specified feature point detection algorithm. The method includes the step of detecting a movement in the set of key points between two frames in a time interval. The method includes the step of, based on the movement of the set of key points between the two frames to infer the motion attributes of the aircraft. The method includes the step of locating aircraft imagery by matching it against a georeferenced satellite imagery database. The method includes the step of combining visual odometry and satellite imagery matching methods to obtain aircraft location. 1. A method for integrating a vision-based navigation system into an aircraft navigation algorithm comprising:obtaining a previous aircraft location, wherein the previous aircraft location comprises a latitude-longitude grid coordinate;{'claim-text': ['using one or more digital cameras to obtain a set of digital images of the landscape beneath the aircraft,', 'identifying a set of key points in the landscape using a specified feature point detection algorithm,', 'detecting a movement in the set of key points between two frames in a time interval,', 'based on the movement of the set of key points between the two frames to infer the motion attributes of the aircraft, and', 'calculating a new latitude-longitude grid coordinates of the aircraft based on the inferred motion attributes of the aircraft,', 'updating the aircraft location as the new latitude-longitude grid coordinates; and'], '#text': 'implementing vision odometry based location determination ...

Systems and Methods for Navigation Path Determination for Unmanned Vehicles

Examples implementations relate to navigation path determination. An example method includes receiving, at a computing system, video data showing a demonstration path for navigating a location. The method further includes identifying, using the video data, a set of permissible surfaces at the location, wherein each permissible surface was traversed by the demonstration path. The method additionally includes determining a navigation path for a vehicle to follow at the location, wherein the navigation path includes a variation from the demonstration path such that the variation causes the vehicle to stay within one or more permissible surfaces from the set of permissible surfaces. The method also includes causing, by the computing system, the vehicle to follow the navigation path to navigate the location.

Systems and methods using image processing to determine at least one kinematic state of a vehicle

System and methods are described that illustrate how to more accurately determine at least one state variable of a vehicle using imaging of a travel way line. Imaging can be used to determine an angle between a longitudinal axis of the travel way line and a longitudinal axis of the vehicle, a shortest distance between the center axis and a reference point on or in the vehicle, and corresponding errors. The determined angle, the determined distance, and the corresponding errors can be used to more accurately determine the at least one state variable.

Sensor perturbation

Perception sensors of a vehicle can be used for various operating functions of the vehicle. A computing device may receive sensor data from the perception sensors, and may calibrate the perception sensors using the sensor data, to enable effective operation of the vehicle. To calibrate the sensors, the computing device may project the sensor data into a voxel space, and determine a voxel score comprising an occupancy score and a residual value for each voxel. The computing device may then adjust an estimated position and/or orientation of the sensors, and associated sensor data, from at least one perception sensor to minimize the voxel score. The computing device may calibrate the sensor using the adjustments corresponding to the minimized voxel score. Additionally, the computing device may be configured to calculate an error in a position associated with the vehicle by calibrating data corresponding to a same point captured at different times.

Map-based adaptive sampling of orientation sensors for positioning

Techniques are provided for adaptively sampling orientation sensors in positioning systems based on location (e.g., map) data. Embodiments can enable a device to use location, direction, and/or location information to anticipate an expected change in motion. The embodiments can then identify and prioritize a number of sampling strategies to alter sampling rates of orientation sensors, and implement at least one strategy, based on priority.

SYSTEMS AND METHODS FOR DETERMINING RECOMMENDED LOCATIONS

A method for determining a recommended location may include identifying a candidate location based on historical order data of a plurality of historical passengers; obtaining a plurality of images showing sights around the candidate location, wherein the plurality of images are captured by at least one vehicle recorder; determining an identification result as to whether a road element is present around the candidate location based on the plurality of images; and determining whether the candidate location is a recommended location based on the identification result. 1. A system for determining a recommended location , comprising:at least one network interface to communicate with at least one vehicle recorder;at least one storage medium including a set of instructions; and identify a candidate location based on historical order data of a plurality of historical passengers;', 'obtain a plurality of images, via the at least one network interface, showing sights around the candidate location, wherein the plurality of images are captured by the at least one vehicle recorder;', 'determine an identification result as to whether a road element is present around the candidate location based on the plurality of images; and', 'determine whether the candidate location is a recommended location based on the identification result., 'at least one processor in communication with the at least one storage medium and operably connected to the at least one network interface, wherein when executing the set of instructions, the at least one processor is directed to2. The system of claim 1 , wherein to determine the identification result claim 1 , the at least one processor is further directed to:for each of the plurality of images, identify whether the road element is present around the candidate location based on a deep learning neural network.3. The system of claim 1 , wherein the identification result is that the road element is not present and the candidate location is determined as ...

Position estimation system, position estimation method and mobile unit

A position estimation system estimates a position of a mobile unit including a camera that captures an image of an area around the mobile unit. The system includes an ECU configured to store a plurality of pieces of map information, the plurality of pieces of map information respectively including a plurality of pieces of image information and respectively including a plurality of pieces of first positional information. The image information corresponding to a plurality of images respectively captured at a plurality of points within a predetermined range, the first positional information being acquired based on information other than the image information and respectively corresponding to the points, environmental conditions of the map information when the images were captured are different from each other, acquire an image captured by the camera, and estimate the position of the mobile unit based on the image acquired by the ECU and the map information.

Techniques for Accurate Pose Estimation in Outdoor Environments

The described technology regards an augmented reality system and method for estimating a position of a location of interest relative to the position and orientation of a display, using a forward buffer to store current and predicted position estimates calculated by the methods of the present invention. Systems of the described technology include including a plurality of sensors, a processing module or other computation means, and a database. Methods of the described technology use data from the sensor package useful to accurately render graphical user interface information on a display.

DEVICE AND METHOD FOR INERTIAL/VIDEO HYBRIDIZATION

The invention relates to an inertial/video hybridisation device () intended to be mounted on a carrier (), the device comprising: a camera () configured to acquire a first image showing a predetermined landmark () attached to the carrier (), a processing unit () configured to estimate a velocity of the carrier () from the acquired first image, with a view to hybridising the estimated velocity with inertial data relating to the carrier () produced by an inertial unit (), locating a position of the landmark () in the first acquired image, calculating a deviation between the located position and a reference position of the landmark (), comparing the calculated deviation with a predetermined threshold, and signalling an alert when the calculated deviation is greater than the predetermined threshold. 1. A device for inertial/video hybridization intended to be embedded on a carrier , the device comprising:a first camera configured to acquire a first image showing a landmark fixed on the carrier,a processing unit configured to estimate a velocity of the carrier from the first image, in order to hybridize the estimated velocity with inertial data relative to the carrier produced by an inertial unit,wherein the processing unit is further configured to:locate a first position of the landmark in the first image,locate a second position of the landmark in the second image,determine a reference position of the landmark by applying to the second position a predetermined transformation representative of a change of frame from the second camera to the first camera,calculate a deviation between the first position and the reference position of the landmark,compare the calculated deviation with a predetermined threshold,signal an alert when the calculated deviation is greater than the predetermined threshold.2. The device according to claim 1 , wherein the reference position of the landmark is a position of the landmark in a reference image acquired by the first camera while the ...

Cradle rotation insensitive inertial navigation

Techniques are provided which may be implemented using various methods and/or apparatuses in a mobile device to provide cradle insensitive inertial navigation. An example method for determining alignment changes between a first body frame and a second body frame according to the disclosure includes obtaining one or more images from an image capture device associated with the first body frame in response to detecting a change in alignment between the first body frame and the second body frame, determining a compensation information based on an analysis of the one or more images, and determining a position based on one or more inertial sensors and the compensation information.

Active image sensing for a navgational system

Systems and methods may selectively collect information from a host vehicle. In one example, a method may include causing collection of navigational information associated with an environment traversed by the host vehicle; storing the collected navigational information; determining, based on an output of at least one navigational sensor, a location of the host vehicle; transmitting the determined location of the host vehicle to a server; receiving, from the server and in response to the transmitted determined location, a request for transmission of a selected subset of the navigational information collected by the host vehicle; and transmitting the selected subset of the navigational information to the server.

Wearable clip for providing social and environmental awareness

A clip includes an IMU coupled to the clip and adapted to detect inertial measurement data and a GPS coupled to the device and adapted to detect location data. The clip further includes a camera adapted to detect image data and a memory adapted to store data. The clip further includes a processor adapted to recognize an object in the surrounding environment by analyzing the data. The processor can determine a desirable action based on the data and a current time or day. The processor can determine a destination based on the determined desirable action. The processor can determine a navigation path based on the determined destination and the data. The processor is further adapted to determine output based on the navigation path. The clip further includes a speaker adapted to provide audio information to the user.

System and method for enhancing non-inertial tracking system with inertial constraints

A system and method for generating a. tracking state for a device includes synchronizing measurement data from exteroceptive sensors and an inertial measurement unit (IMU). A processing unit is programmed to offset one of the measurement signals by a time offset that minimizes a total error between a change in rotation of the device predicted by the exteroceptive sensor data over a time interval defined by an exteroceptive sensor sampling rate and a change in rotation of the device predicted by the IMU sensor data over the time interval.

IMAGING FOR NAVIGATION SYSTEMS AND METHODS

Techniques are disclosed for systems and methods to provide passage planning for a mobile structure. A passage planning system includes a logic device configured to communicate with a user interface associated with the mobile structure and at least one operational state sensor mounted to or within the mobile structure. The logic device determines an operational range map based, at least in part, on an operational state of the mobile structure and/or environmental conditions associated with the mobile structure. Such operational range map and other control signals may be displayed to a user and/or used to generate a planned route and/or adjust a steering actuator, a propulsion system thrust, and/or other operational systems of the mobile structure. 1. A method comprising:receiving orientation data from an orientation sensor coupled to a mobile structure;determining a boresight roll of an imaging module of an imaging system coupled to mobile structure based, at least in part, on the received orientation data, wherein an imaging module is disposed within a sealed enclosure and configured to capture image data along an optical axis of the imaging system according to a field of view (FOV) of the imaging module; andcontrolling a mechanical roll stabilizer of the imaging system coupled to the imaging module to compensate for the determined boresight roll, wherein the mechanical roll stabilizer is disposed within the sealed enclosure and is configured to provide mechanical roll stabilization of the imaging module with respect to the optical axis of the imaging system.2. The method of claim 1 , wherein the controlling the mechanical roll stabilizer comprises:generating a control signal based, at least in part, on the determined boresight roll and providing the control signal to an actuator of the mechanical roll stabilizer to rotate the imaging module to compensate for the determined boresight roll.3. The method of claim 1 , wherein:the controlling the mechanical roll ...

Iterative estimation of non-holonomic constraints in an inertial navigation system

A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals, each set corresponding to location data and being received based on a sampling interval. The at least one processor is configured to, for each sampling period defined by the sampling interval, obtain sensor data corresponding to device motion during the sampling period, determine an orientation of the device relative to that of the vehicle based on the sensor data, calculate a non-holonomic constraint based on the orientation of the device relative to that of the vehicle such that the non-holonomic constraint is iteratively updated, and estimate a device state based on the non-holonomic constraint.

Dead reckoning positional prediction for augmented reality and virtual reality applications

Techniques for predicting a virtual camera view in an augmented reality (AR) or virtual reality (VR) application. A first change in position of a user device over a first time period is determined based on analyzing a plurality of frames of image data related to an AR or VR application. A dead reckoning calculation is used to predict a second change in position of the user device over a second time period, based on the first change in position and data received from an Inertial Measurement Unit (IMU) associated with the user device. A plurality of frames of image data are generated for display in the AR or VR application, based on the predicted second change in position of the user device.

Methods and systems for geometrical optics positioning using spatial color coded leds

A method and system of indoor positioning associated with a smartphone includes installing one or more color LED identifiers on a ceiling associated with an indoor location and dividing the indoor location based on the one or more color LED identifiers into one or more cells. One or more images of the one or more color LED identifiers are captured through a camera associated with the smartphone. Further, accelerometer data associated with the smartphone is captured onto a memory associated with the smartphone. The accelerometer data and captured images are transmitted over a computer network to a computer processor and one or more of a location (two dimensional and/or three dimensional) in one or more cells, azimuth and tilt associated with the smartphone are calculated through closed form equations. The location of the smartphone is determined within the cell based on an identified cell of the one or more cells.

Hybrid photo navigation and mapping

Embodiments disclosed obtain a plurality of measurement sets from a plurality of sensors in conjunction with the capture of a sequence of exterior and interior images of a structure while traversing locations in and around the structure. Each measurement set may be associated with at least one image. An external structural envelope of the structure is determined from exterior images of the structure and the corresponding outdoor trajectory of a UE. The position and orientation of the structure and the structural envelope is determined in absolute coordinates. Further, an indoor map of the structure in absolute coordinates may be obtained based on interior images of the structure, a structural envelope in absolute coordinates, and measurements associated with the indoor trajectory of the UE during traversal of the indoor area to capture the interior images.

Exterior hybrid photo mapping

Embodiments disclosed pertain to the use of user equipment (UE) for the generation of a 3D exterior envelope of a structure based on captured images and a measurement set associated with each captured image. In some embodiments, a sequence of exterior images of a structure is captured and a corresponding measurement set comprising Inertial Measurement Unit (IMU) measurements, wireless measurements (including Global Navigation Satellite (GNSS) measurements) and/or other non-wireless sensor measurements may be obtained concurrently. A closed-loop trajectory of the UE in global coordinates may be determined and a 3D structural envelope of the structure may be obtained based on the closed loop trajectory and feature points in a subset of images selected from the sequence of exterior images of the structure.

Using optical sensors to resolve vehicle heading issues

A control system fuses different sensor data together to determine an orientation of a vehicle. The control system receives visual heading data for the vehicle from a camera system, global navigation satellite system (GNSS) heading data from a GNSS system, and inertial measurement unit (IMU) heading data from an IMU. The control system may assign weights to the visual, GNSS, and IMU heading data based on operating conditions of the vehicle that can vary accuracy associated with the different visual, GNSS, and IMU data. The control system then uses the weighted visual, GNSS, and IMU data to determine a more accurate vehicle heading.

STRUCTURE FROM MOTION (SfM) PROCESSING FOR UNMANNED AERIAL VEHICLE (UAV)

A method of imaging an area using an unmanned aerial vehicle (UAV) collects a plurality of images from a sensor mounted to the UAV. The plurality of images are processed to detect regions that require additional imaging and an updated flight plan and sensor gimbal position plan is created to capture portions of the area identified as requiring additional imaging.

Method of accelerating simultaneous localization and mapping (slam) and device using same

A preconditioned conjugate gradient (PCG) solver, embedded in an electronic device to perform a simultaneous localization and mapping (SLAM) operation, includes an image database, a factor graph database, and a back-end processor, wherein the back-end processor is configured to receive an image from the image database to perform re-localization, receive, from the factor graph database, data for calculating six degrees of freedom (DoF)-related components, construct a matrix including the six degrees of freedom-related components based on the received data, and load and rearrange the matrix and a vector, to perform calculation on each block of each row of the matrix and the vector, then output first data, and shift second data to a location of the first data.

System having travel guidance and reality games

A system includes a server, a mobile device with a positioning unit, and an operation module. The server has a mascot database and a map database where main areas are defined. The positioning unit determines a current location of the mobile device for navigation. The operation module includes a mascot collecting unit linked to the mascot database, a photograph collecting unit linked to the map database, and a camera module connected to both collecting units. When the current location corresponds to a main position of one main area, at least one mascot linked to the main area is incorporated into the mascot collecting unit so that the mascot, a real scene of the main area, and the user are caught in a frame by the camera module to form and store a picture in the photograph collecting unit, thereby enjoying collecting mascots and combining travel guidance with reality games.

Method and apparatus for outputting pose information

A method and apparatus for outputting pose information selects first points from a frames captured by a first sensor, estimates rotation information between the frames based on motion information sensed by a second sensor, corrects the estimated rotation information based on third points, the third points being remaining points when second points corresponding to a dynamic object are excluded from the first points, obtains translation information between the frames based on the third points and the corrected rotation information, and outputs the corrected rotation information and the translation information.

Inertia-based navigation apparatus and inertia-based navigation method based on relative preintegration

An inertia-based navigation apparatus and an inertia-based navigation method based on relative preintegration are provided. The inertia-based navigation apparatus includes: a first sensor detecting and outputting motion information about a moving body which is moving, based on a first coordinate system; a second sensor detecting and outputting inertia data about a translational acceleration and a rotational angular velocity related to the movement of the moving body, based on a second coordinate system; and a controller determining, at every first time, pose information about a position, a velocity and an attitude of the moving body in a reference coordinate system, based on the motion information and the inertia data.

INFORMATION PROCESSING APPARATUS, MOBILE OBJECT, CONTROL SYSTEM, INFORMATION PROCESSING METHOD, AND PROGRAM

[Solving Means] [Object] To provide an information processing apparatus, a mobile object, a system, an information processing method, and a program that make it possible to reduce an impact of a disturbance factor. [Solving Means] An information processing apparatus includes an information acquisition unit and a control prediction unit. The information acquisition unit acquires information regarding a location and a posture of a first mobile object that includes a sensing device. The control prediction unit predicts control performed with respect to the sensing device, on the basis of the information regarding the location and the posture and map information, the information regarding the location and the posture being acquired by the information acquisition unit. 1. An information processing apparatus comprising:an information acquisition unit that acquires information regarding a location and a posture of a first mobile object that includes a sensing device; anda control prediction unit that predicts control performed with respect to the sensing device, on a basis of the information regarding the location and the posture and map information, the information regarding the location and the posture being acquired by the information acquisition unit.2. The information processing apparatus according to claim 1 , whereinthe sensing device includes an image-capturing device, a unit for predicting a location and a posture of a mobile object that predicts the location and the posture of the first mobile object on a basis of the information regarding the location and the posture, the information regarding the location and the posture being acquired by the information acquisition unit, and', 'a unit for predicting a position of a disturbance factor that predicts a position of a disturbance factor in an image captured by the image-capturing device, on a basis of the map information and a result of the prediction performed by the unit for predicting a location and a posture of ...

Range image aided ins with map based localization

A navigation system includes an IMU, a navigation estimator configured to estimate a current navigation solution based on (i) a previous navigation solution, and (ii) a specific force vector and an angular rate vector measured by the IMU, an RI sensor, an RI data preprocessor configured to perform an a priori transformation of RI data acquired by the RI sensor using the current navigation solution to obtain transformed RI data, an RI map database configured to retrieve a valid keyframe map based on the transformed RI data, and an RI filter manager (RFM) configured to construct a map registration cost gradient (MRCG) measurement based on (i) the transformed RI data, and (ii) the known position and the known orientation of the valid keyframe map. The navigation estimator is further configured to determine an absolute navigation solution based on at least (i) the current navigation solution, and (ii) the MRCG measurement.

Discovering and plotting the boundary of an enclosure

Provided is a process that includes: obtaining a first version of a map of a workspace; selecting a first undiscovered area of the workspace; in response to selecting the first undiscovered area, causing the robot to move to a position and orientation to sense data in at least part of the first undiscovered area; and obtaining an updated version of the map mapping a larger area of the workspace than the first version.

RANGE IMAGE AIDED INS

A navigation system includes an IMU, a navigation estimator configured to estimate a current navigation solution based on (i) a last navigation solution, and (ii) a specific force vector and a n angular rate vector measured by the IMU, an RI sensor, an RI data preprocessor configured to: perform a priori transformations of last RI data and current RI data to obtain transformed last RI data and transformed current RI data based on the last navigation solution and the current navigation solution, respectively, an RI filter manager (RFM) configured to construct a delta pose registration cost gradient (DPRCG) measurement based on (i) the transformed last RI data, (ii) the transformed current RI data, (iii) the current navigation solution, and (iv) the last navigation solution. The navigation estimator is further configured to determine an absolute navigation solution based on at least (i) the current navigation solution, and (ii) the DPRCG measurement. 1. A navigation system comprising:an inertial measurement unit (IMU) attached to a dynamic platform and configured to measure a specific force vector and an angular rate vector of the dynamic platform; determine an INS solution of a position and an orientation of the dynamic platform based on at least: (i) a previous INS solution, and (ii) the specific force vector and the angular rate vector measured by the IMU;', 'compute a current INS solution based on the INS solution, the current INS solution being valid at a current construction time; and', 'compute a last INS solution based on a prior INS solution, the last INS solution being valid at a last construction time prior to the current construction time;, 'an inertial navigation system (INS) unit coupled to the IMU, the INS unit configured toa range image sensor (RI sensor) attached to the dynamic platform and configured to acquire last range image data (RI data) at the last construction time and current RI data at the current construction time; perform an a priori ...

System for sensing vehicle motion and environmental conditions

A system and method for deterring theft of a marine vehicles is provided. The system is designed to collect barometric pressure data and analyze it to determine whether there has been a sudden change in elevation that may be indicative of a theft. The system is also designed to collect environmental data pertaining to a marine vehicle's normal environment and compare it to a normal environmental state of the marine vehicle in order to detect changes that may be indicative of a theft. Additionally, the system is designed to monitor equipment of the marine vehicle and alert a user if the equipment has been moved in a way that may be indicative of a theft. When the system determines an event has occurred that may be indicative of a theft, the system may alert the user by triggering an alarm via a computer readable signal.

Apparatus, systems and methods for shared viewing experience using head mounted displays

Systems and methods are operable to share a viewing experience of a free viewpoint format media content event. An exemplary embodiment receives the free viewpoint format media content event, receives unique geometric orientation information from each one of a plurality of head mounted displays (HMDs), determines a unique viewpoint location for each one of the plurality of HMDs based upon the geometric orientation information received from each one of the plurality of HMDs, determines a unique viewpoint area for each one of the plurality of HMDs based upon the determined unique viewpoint location, and communicates each one of the unique viewpoint areas to the associated one of the plurality of HMDs.

High Bandwidth And Low Latency Hybrid Communication Techniques For A Navigation System

High bandwidth, low latency hybrid communication techniques are disclosed for a navigation system. The navigation system comprises a tracker configured to couple to the object and a localization device configured to track the tracker. In one embodiment, the localization device is configured to utilize communication on a first spectrum to track the tracker and to manage an operating parameter of the tracker with respect to communication on a second spectrum. In another embodiment, the localization device is configured to utilize communication with a first modulation method to track the tracker and to manage an operating parameter of the tracker and to utilize communication with a second modulation method for receiving sensor data from the tracker.

VEHICLE POSITION ESTIMATION DEVICE AND VEHICLE CONTROL DEVICE

A vehicle position estimation device according to an example of an embodiment includes a parking lot data acquisition unit that acquires parking lot data capable of identifying an absolute orientation and an absolute position of a road surface marking provided on a road surface of a parking lot, an image data acquisition unit that acquires image data obtained by an on-board camera that captures a situation around a vehicle, and a position estimation unit that calculates a relative orientation and a relative position of the road surface marking with respect to the vehicle on the image data by detecting road surface marking data related to the road surface marking from the image data, and that estimates an actual orientation and an actual position of the vehicle on the basis of the calculated relative orientation, the calculated relative position, and the parking lot data. 1. A vehicle position estimation device comprising:a parking lot data acquisition unit that acquires parking lot data capable of identifying an absolute orientation and an absolute position of a road surface marking provided on a road surface of a parking lot;an image data acquisition unit that acquires image data obtained by an on-board camera that captures a situation around a vehicle; anda position estimation unit that calculates a relative orientation and a relative position of the road surface marking with respect to the vehicle on the image data by detecting road surface marking data related to the road surface marking from the image data, and that estimates an actual orientation and an actual position of the vehicle on the basis of the calculated relative orientation, the calculated relative position, and the parking lot data.2. The vehicle position estimation device according to claim 1 , whereinthe position estimation unit calculates the relative orientation and the relative position of the road surface marking that is located on either a left side or a right side of the vehicle by ...

Apparatus of controlling movement of mobile robot mounted with wide angle camera and method thereof

Disclosed are an apparatus of controlling movement of a mobile robot mounted with a wide angle camera and a method thereof. An apparatus of recognizing a position of a mobile robot includes two wide angle cameras which obtain one pair of stereo images on a region of interest including a vertical direction and a horizontal direction in accordance with movement of a mobile robot; an inertial measurement unit (IMU) which obtains inertial information of a mobile robot; a position recognizing unit which predicts a movement point using one between first odometry information calculated based on at least one pair of stereo images and second odometry information calculated based on the inertial information and estimates a current position using the predicted movement point and a previously stored key frame, by a position recognizing unit; and a movement control unit which controls movement of the mobile robot based on the estimated position.

METHODS AND APPARATUS FOR DYNAMIC OPTICAL FLOW SENSOR CALIBRATION BY IMU IN PLANAR ROBOT SYSTEMS

Methods, apparatus, and systems are provided for calibrating an optical flow (OF) sensor by using an inertial measurement unit (IMU) measurements in a planar robot system. 1. A method of calibrating an optical flow (OF) sensor by using an inertial measurement unit (IMU) in a robot system , the method comprising:performing measurements to collect data from an IMU; andmodifying one or more of optical flow scales, an alignment angle, and/or displacement between the IMU and the OF sensor using the data to calibrate the OF sensor.2. The method of claim 1 , wherein the step of calibrating optical flow scales claim 1 , an alignment angle claim 1 , and/or displacement between the IMU and the OF sensor further comprises:using fminsearch and/or a Least Squares (LS) process in one or more formulations, via at least a formulation of a rigid body equation in a predetermined domain and a predetermined frame.3. The method of claim 1 , wherein the IMU measures a linear acceleration and/or an angular velocity.4. The method of claim 1 , wherein the IMU obtains an angular position.5. The method of claim 2 , wherein the predetermined domain is an acceleration domain claim 2 , a velocity domain claim 2 , and/or a position domain.6. The method of claim 2 , wherein the predetermined frame is a body frame or a user frame.7. The method of claim 1 , wherein the calibration comprises:relating IMU and OF sensor measurements through the rigid body equation in a body frame and a velocity domain.8. The method of claim 1 , wherein the calibration comprises:receiving, from the IMU, a first signal including a linear acceleration;receiving, from the OF sensor, a second signal including a velocity of the robot system;receiving, from the IMU, a third signal including a vector generated based on an angular velocity and a known vector;after rotating to a user frame, applying a first set of direct-current (DC) block filters to the first signal, the second signal, and the third signal; andintegrating the ...

Accuracy of global navigation satellite system based positioning using high definition map based localization

A vehicle, for example, an autonomous vehicle receives signals from a global navigation satellite system (GNSS) and determines accurate location of the vehicle using the GNSS signal. The vehicle performs localization to determine the location of the vehicle as it drives. The autonomous vehicle uses sensor data and a high definition map to determine an accurate location of the autonomous vehicle. The autonomous vehicle uses accurate location of the vehicle to determine RTK corrections that is used for improving GNSS location estimates at a future location. The RTK corrections may be transmitted to other vehicles.

Signal processing device, detection device, sensor, electronic apparatus and moving object

A signal processing device includes a Kalman filter that extracts a DC component of an input signal by performing Kalman filter processing on the basis of observation noise and system noise which are estimated from the input signal.

Apparatus and method for data-based referenced navigation

A method is provided. The method comprises: initializing a point mass filter; initializing the one or more Bayesian filters; obtaining measurement data associated with a horizontal position on a surface; obtaining measurement data of a horizontal position and a velocity; obtaining geo-mapping data; estimating, with the point mass filter, the horizontal position on the surface based upon the geo-mapping data and the measurement data; estimating, with the one or more Bayesian filters, remaining state parameters based upon an output of the point mass filter and the measurement data; predicting, with the point mass filter, an a priori horizontal position, on a surface for a future time when the next measurement data will be obtained; and predicting, with the one or more Bayesian filters, an a priori remaining state parameters for a future time when the next measurement data will be obtained.

VEHICULAR COMPONENT CONTROL USING MAPS

Method and system for adjusting a vehicular component based on vehicle position includes obtaining kinematic data from an inertial measurement unit (IMU), deriving, using a processor, information about current vehicle position from the data obtained from the IMU and an earlier known vehicle position, and adjusting the derived current vehicle position to obtain a corrected current vehicle position. The latter is achieved by obtaining images of an external vehicle area using a camera assembly in a fixed relationship to the IMU, identifying multiple landmarks in each image, analyzing each image to derive positional information about each landmark, identifying discrepancies between image-derived positional information about each landmark and positional information about the same landmark obtained from a map database, and adjusting the derived current vehicle position based on identified discrepancies to obtain the corrected current vehicle position. Operation of the component is changed based on the corrected current vehicle position. 1. A method for adjusting a vehicular component , comprising:deriving, using a processor, information about current vehicle position from data obtained from an inertial measurement unit on the vehicle and an earlier known vehicle position; obtaining images of an area external of the vehicle using at least one camera assembly on the vehicle, each of the at least one camera assembly being in a fixed relationship to the inertial measurement unit;', 'analyzing, using the processor, a plurality of the obtained images to derive positional information about a common landmark from a combination of two of the plurality of obtained images that include the common landmark, which constitutes image-derived positional information;', 'obtaining from a map database, positional information about the common landmark, which constitutes database-obtained positional information;, 'adjusting, using the processor, the derived current vehicle position to obtain a ...

Vehicle Localization Apparatus and Method

A vehicle localization method includes obtaining a stereo image while a vehicle is driven, extracting a matching vector from the stereo image while the vehicle is driven, loading a map vector of a current location based on GPS information in previously constructed map data, matching the extracted matching vector with the map vector, and estimating a positioning coordinate corresponding to the extracted matching vector as a current location of the vehicle when the extracted matching vector and the map vector meet a condition.

System and method for assisted extravehicular activity self-return

A system and method for assisted EVA self-return is provided herein. The system estimates a crewmember's navigation state relative to a fixed location, for example on an accompanying orbiting spacecraft, and computes a guidance trajectory for returning the crewmember to that fixed location. The system may account for safety and clearance requirements while computing the guidance trajectory. According to at least one embodiment, the system actuates the crewmember's safety jetpack to follow the prescribed trajectory to the fixed location. In another embodiment, the system provides the crewmember with a directional cue (e.g., a visual, auditory, or tactile cue) corresponding to the prescribed trajectory back to the fixed location. The system may be activated by the crewmember or remotely by another crewmember and/or system.

3-d motion estimation and online temporal calibration for camera-imu systems

A system and method for a 3-D motion estimation and online temporal calibration having one or more than one processor, one or more than one camera, one or more than one inertial sensor, a storage for storing data and instructions. The stored instructions comprise a filter estimation module, high-precision navigation instructions and consistent state estimates in scenarios involving features, with both constant and time-varying offsets from the filter estimation module.

Imu data offset compensation for an autonomous vehicle

A sensor data processing system of an autonomous vehicle can receive inertial measurement unit (IMU) data from one or more IMUs of the autonomous vehicle. Based at least in part on the IMU data, the system can identify an IMU data offset from a deficient IMU of the one or more IMUs, and generate an offset compensation transform to compensate for the IMU data offset from the deficient IMU. The system may then dynamically execute the offset compensation transform on the IMU data from the deficient IMU to dynamically compensate for the IMU data offset.

Object linking method, object linking apparatus, and storage medium

An object linking method including: detecting each first object based on a video image, detecting each second object based on each data measured by each inertial sensor, each first object or each second object having each first state or each second state that is one of states including a moving state and a stopping state, and linking, by a computer, each first object and each second object in one-to-one, based on each first change of each first state and each second change of each second state, wherein when a specified first object of at least one first object is not linked to any of the at least one second object, the specified first object is linked to a virtual second object that is added to the at least one second object.

Methods and apparatuses for location-triggered sensor initialization

Methods, apparatuses, and devices for generating one or more harsh or diminished radiofrequency environments relative to a planned route of a mobile device user. In one example, a mobile device user a be routed through a harsh or diminished radiofrequency environment based, at least in part, on a sensor suite of a mobile device and/or based on a user's preferences. Prior to entry into such an environment, various sensors may be activated in a manner that permits position estimation in an absence of SPS based positioning signals and/or TPS based positioning signals.

Automatic Working System, Self-Moving Device And Control Method Thereof

The present invention relates to a self-moving device moving and working in a work area defined by a border, includes: a housing; a moving module, mounted in the housing, and driven by a drive motor to drive the self-moving device to move; a control module, controlling the self-moving device to move and work; a satellite navigation device, receiving a satellite signal; at least one position sensor, detecting a feature related to a position of the self-moving device; and a fusion processing unit comprising at least two inputs, one is the satellite signal, and the other is an output of the position sensor; the fusion processing unit performs operation on the satellite signal and the output of the position sensor, and outputs position information of the self-moving device; and the control module controls the moving module to drive the self-moving device to move based on the position information.

Gyroscope assisted scalable visual simultaneous localization and mapping

An indoor localization system uses Visual Simultaneous Localization and Mapping (VSLAM) aided by gyroscope sensor information. Indoor environments pose several challenges which could cause a vision only system to fail due to tracking errors. Investigation revealed significant feature loss in a vision only system when traversing plain walls, windows and staircases. However, the addition of a gyroscope helps in handling such difficult conditions by providing additional rotational information. A portable system consisting of an Inertial Measurement Unit (IMU) and a stereo camera has been developed for indoor mapping. The images and gyroscope rates acquired by the system are stored and post-processed using Gyroscope Assisted Scalable Visual Simultaneous Localization and Mapping Algorithm.

STRUCTURE FROM MOTION (SfM) PROCESSING FOR UNMANNED AERIAL VEHICLE (UAV)

A method of imaging an area using an unmanned aerial vehicle (UAV) collects a plurality of images from a sensor mounted to the UAV. The plurality of images are processed to detect regions that require additional imaging and an updated flight plan and sensor gimbal position plan is created to capture portions of the area identified as requiring additional imaging.

Mobile device tethering for a remote parking assist system of a vehicle

Method and apparatus are disclosed for mobile device tethering for a remote parking assist system of a vehicle. A vehicle includes a camera and a body control module. The body control module sends an instruction to a mobile device and captures, with the camera, an image of the mobile device. The body control module also analyzes the image to determine an initial location of the mobile device relative to the vehicle, and based on the initial location, performs dead reckoning on the mobile device to track the mobile device. When the mobile device is within a threshold distance, the body control module enables autonomous parking.

System and method for estimation of machine position

A system is provided. The system includes a perception sensor, a first inertial measurement unit and a first localization module. The first localization module is configured to generate a first position estimate signal indicative of an estimated position of the machine. The system includes a second inertial measurement unit and a second localization module. The second localization module is configured to generate a second position estimate signal indicative of the estimated position of the machine. A position determination module is communicably coupled to the first and second localization modules. The position determination module is configured to determine a health of the first and second localization modules based on one or more parameters indicative of errors associated with the first and second inertial measurement units respectively; and determine an estimated position of the machine based on the determined health of the first and second localization modules.

Mobile mapping system

Embodiments of systems and methods for a mobile mapping system are described. In an embodiment, a method includes capturing a plurality of images of an object point using a mobile computing platform. The method may also include determining an initial set of orientation parameters in response to one or more orientation sensors on the mobile computing platform. Additionally, the method may include calculating a corrected set of orientation parameters by matching object points in the plurality of images. Further, the method may include estimating a three-dimensional ground coordinate associated with the captured images in response to the corrected set of orientation parameters.

MULTIPLE VIEW TRIANGULATION WITH IMPROVED ROBUSTNESS TO OBSERVATION ERRORS

Triangulation is applied, by a method and a device, to determine a scene point location in a global coordinate system, GCS, based on location coordinates for observed image points in plural views of a scene, and global-local transformation matrices for the views. The local coordinates are given in local coordinate systems, LCSs, arranged to define distance coordinate axes that are perpendicular to image planes of the views. The scene point location is determined by minimizing a plurality of differences between first and second estimates of the scene point location in the LCSs, the first estimates being given by linear scaling of the location coordinates, and the second estimate being given by operating the transformation matrices on the scene point location. An improved robustness to observation errors is achieved by defining the plurality of differences to penalize differences that includes the linear scaling as applied along the distance coordinate axes. 1. A method of determining a location of a scene point in a global coordinate system , said method comprising:obtaining location data for image points that represent the scene point in a plurality of overlapping views, the location data comprising location coordinates of a respective image point in a local coordinate system of a respective view, the local coordinate system comprising a distance coordinate axis that is perpendicular to a predefined image plane of the respective view;obtaining a transformation matrix of the respective view, the transformation matrix defining a transformation operation between the local coordinate system of the respective view and the global coordinate system; anddetermining the location of the scene point in the global coordinate system;wherein said determining comprises minimizing a plurality of differences between first and second estimated locations of the scene point in the local coordinate system of the respective view, wherein the first estimated location is given by a linear ...

Visual-inertial sensor fusion for navigation, localization, mapping, and 3d reconstruction

A new method for improving the robustness of visual-inertial integration systems (VINS) based on derivation of optimal discriminants for outlier rejection, and the consequent approximations, that are both conceptually and empirically superior to other outlier detection schemes used in this context. It should be appreciated that VINS is central to a number of application areas including augmented reality (AR), virtual reality (VR), robotics, autonomous vehicles, autonomous flying robots, and so forth and their related hardware including mobile phones, such as for use in indoor localization (in GPS-denied areas), and the like.

Systems, methods, and apparatus for providing indoor navigation using optical floor sensors

An apparatus includes (i) an absolute position sensor coupled to a case, the position sensor including a light sensor, and circuitry configured to determine an identifier within a barcode, the individual bars of the barcode being sensed by the light sensor, and (ii) a motion sensor coupled to the case, the motion sensor including a first magnetic field sensor, a code wheel having two or more magnets positioned to rotate in unison with a wheel of the moveable object, and encoder circuitry configured to determine an amount of rotation of the wheel of the moveable object based on an output of the first magnetic field sensor.

Augmented reality labels systems and methods

Techniques are disclosed for systems and methods for labeling objects displayed by an augmented reality display system used to assist in the operation of mobile structures. Such an augmented reality display system includes a logic device configured to communicate with navigational sensors and imaging modules coupled to a mobile structure, where the navigational sensors are configured to provide navigational data associated with the mobile structure and the imaging module is configured to image a scene from a position on the mobile structure. The logic device is configured to detect an object in the scene, determine a heading reliability associated with the detected object based, at least in part, on the navigational data, and render an integrated model of the scene on a display, where the integrated model is configured to indicate the determined heading reliability associated with the detected object.

Scene recognition using volumetric substitution of real world objects

Techniques are provided to estimate of location or position of objects that are depicted in an image of a scene. Some implementations include obtaining an image of a scene; identifying an object within the image of the scene; obtaining a three-dimensional model that corresponds to the object that was identified within the image of the scene, the three-dimensional model being obtained from the database of three-dimensional models; determining, based on data from the three-dimensional model, an estimated depth of the object within the scene; generating or updating a three-dimensional representation of the scene based at least on the estimated depth of the object within the scene; and providing the three-dimensional representation of the scene, including at least a portion of the three-dimensional representation of the scene that was generated or updated based on the three-dimensional model of the object, to the scene analyzer.

Robot Localization Using Variance Sampling

A method of localizing a robot includes receiving odometry information plotting locations of the robot and sensor data of the environment about the robot. The method also includes obtaining a series of odometry information members, each including a respective odometry measurement at a respective time. The method also includes obtaining a series of sensor data members, each including a respective sensor measurement at the respective time. The method also includes, for each sensor data member of the series of sensor data members, (i) determining a localization of the robot at the respective time based on the respective sensor data, and (ii) determining an offset of the localization relative to the odometry measurement at the respective time. The method also includes determining whether a variance of the offsets determined for the localizations exceeds a threshold variance. When the variance among the offsets exceeds the threshold variance, a signal is generated.

System for determining hitch angle

A system for determining a hitch angle between a vehicle and trailer is provided. The system includes an imaging device disposed on the trailer. A first navigation system is disposed on-board the vehicle. A second navigation system is integrated with the imaging device. A controller determines the hitch angle based on data received from the first navigation system and the second navigation system.

System and method for localizing a trackee at a location and mapping the location using transitions

A system and method for recognizing features for location correction in Simultaneous Localization And Mapping operations, thus facilitating longer duration navigation, is provided. The system may detect features from magnetic, inertial, GPS, light sensors, and/or other sensors that can be associated with a location and recognized when revisited. Feature detection may be implemented on a generally portable tracking system, which may facilitate the use of higher sample rate data for more precise localization of features, improved tracking when network communications are unavailable, and improved ability of the tracking system to act as a smart standalone positioning system to provide rich input to higher level navigation algorithms/systems. The system may detect a transition from structured (such as indoors, in caves, etc.) to unstructured (such as outdoor) environments and from pedestrian motion to travel in a vehicle. The system may include an integrated self-tracking unit that can localize and self-correct such localizations.

Self-Position Estimation Method and Self-Position Estimation Device

A self-position estimation method includes: detecting a relative position of each target existing around a moving body relative to the moving body; estimating a movement amount of the moving body; correcting the relative position on a basis of the movement amount of the moving body and accumulating the corrected relative position as target position data; detecting a slope amount of a traveling road of the moving body; selecting, from among the accumulated target position data, the target position data of one or more targets in one or more sections having a slope amount less than a threshold value; and collating the selected target position data with map information indicating positions of the targets on a two-dimensional map to estimate a present position of the moving body.

Drone provided with a vertical-view video camera compensated for the instantaneous rotations for estimation of the horizontal speeds

A vertical-view camera ( 16 ) delivers an image signal (S camV ) of the ground overflown by the drone. Gyrometric sensors ( 102 ) measure the Euler angles (φ, θ, Ψ) characterizing the attitude of the drone and delivering a gyrometric signal (S gyro ) representative of the instantaneous rotations. Rotation compensation means ( 136 ) receive the image signal and the gyrometric signal and deliver retimed image data, compensated for the rotations, then used to estimate the horizontal speeds of the drone. The camera and the inertial unit are piloted by a common clock ( 160 ), and it is provided a circuit ( 170 ) for determining the value of the phase-shift between the gyrometric signal and the image signal, and to apply this phase-shift value at the input of the rotation compensation means ( 136 ) to resynchronize the image signal onto the gyrometric signal before computation of the retimed image data.

Localized Map Generation

A method of creating a local map includes: receiving, at a mobile electronic data processing apparatus, a request from a server to generate a map of a specified destination; sending to the server a message accepting the request to generate the map responsive to receiving, at a user input of the mobile electronic data processing device, a user command indicating acceptance of the request; generating, using a processor, information related to construction of the map; an transmitting, from the mobile electronic data processing apparatus, the information related to construction of the map.

Autonomously operated dirigible

Propulsion of an unmanned vehicle may include determining and ordering a subset of altitude-differentiated wind vectors, the subset facilitating directional air flow from a starting geographic region to a destination geographic region, and configuring the vehicle and adjusting the altitude of the vehicle to the altitude corresponding to each of the subset of wind vectors as ordered based on a flight plan that includes at least one of a duration and distance for each of the ordered subset of the wind vectors.

Registration for vehicular augmented reality using auto-harmonization

A method, a system, and a computer program product for tracking an object moving relative to a moving platform, the moving platform moving relative to an external frame of reference. The system includes An inertial sensor for tracking the object relative to the external reference frame, a non-inertial sensor for tracking the object relative to the moving platform, and a processor to perform sensor fusion of the inertial and non-inertial measurements in order to accurately track the object and concurrently estimate the misalignment of the non-inertial sensor's reference frame relative to the moving platform.

Navigation system for GPS denied environments

Methods and apparatus for providing self-contained guidance, navigation, and control (GN&C) functions for a vehicle moving through an environment on or near the ground, in the air or in space without externally provided information are disclosed. More particularly, one embodiment of the present invention includes a Heading Sensor ( 36 ), an Absolute Location Sensor ( 38 ), a timer ( 40 ), a Range Doppler Processor ( 42 ), a Navigation Reference Sensor ( 44 ), an Area Range and a Velocity Sensor ( 46 ) which provide enhanced navigation information about a universal reference frame ( 22 ) and one or more targets ( 20 ).

System and method for lidar-based vehicular localization relating to autonomous navigation

A system for use in a vehicle, the system comprising one or more sensors, one or more processors operatively coupled to the one or more sensors, and a memory including instructions, which when executed by the one or more processors, cause the one or more processors to perform a method. The method comprising capturing a current point cloud with the one or more sensors, determining an estimated location and an estimated heading of the vehicle, selecting one or more point clouds based on the estimated location and heading of the vehicle, simplifying the current point cloud and the one or more point clouds, correlating the current point cloud to the one or more point clouds, and determining an updated estimate of the location of the vehicle based on correlation between the current point cloud and the one or more point clouds.

Methods and Systems for Calibrating Sensors Using Recognized Objects

Methods and systems for sensor calibration are described. An example method involves receiving image data from a first sensor and sensor data associated with the image data from a second sensor. The image data includes data representative of a target object. The method further involves determining an object identification for the target object based on the captured image data. Additionally, the method includes retrieving object data based on the object identification, where the object data includes data related to a three-dimensional representation of the target object. Additionally, the method includes determining a predicted sensor value based on the based on the object data and the image data. Further, the method includes determining a sensor calibration value based on a different between the received sensor data and the predicted sensor value. Moreover, the method includes adjusting the second sensor based on the sensor calibration value.

Miniature vision-inertial navigation system with extended dynamic range

A system and method for tracking positions of objects in an actual scene in a wide range of lighting conditions. A vision-inertial navigation system is provided that may be configured to track relative positions of objects of interest in lighting conditions ranging from, e.g., typical indoor lighting conditions to direct sunlight to caves with virtually with no light. The navigation system may include two or more helmet-mounted cameras each configured to capture images of the actual scene in a different lighting condition. A remote processing element may combine data from the two or more helmet-mounted cameras with data from a helmet-mounted inertial sensor to estimate the position (e.g., 3D location) of the objects. The navigation system may display the estimated position for each object on a transparent display device such that, from a user's perspective, the estimated position for each object is superimposed onto the corresponding object and/or other information relating to the user's and/or object's position is displayed.

Positioning method and apparatus

The present invention discloses a positioning method and apparatus. The method includes: acquiring a first image captured by an optical device, where the first image includes an observation object and a plurality of predetermined objects, and the predetermined objects are objects with known geographic coordinates; selecting a first predetermined object from the predetermined objects based on the first image; acquiring a second image, where the first predetermined object is located in a center of the second image; determining a first attitude angle of the optical device based on the first predetermined object in the second image and measurement data captured by an inertial navigation system; modifying the first attitude angle based on a positional relationship between the observation object and the first predetermined object in the second image, to obtain a second attitude angle; and calculating geographic coordinates of the observation object based on the second attitude angle. According to the present invention, a prior-art technical problem that costs of accurately locating an observation object are high is resolved.

Visual Object Tracker

A method for tracking a trailer coupler positioned behind a tow vehicle is provided. The method includes receiving one or more images from a camera positioned on a back portion of the tow vehicle. The method also includes determining a trailer coupler position within the one or more images. The trailer coupler position associated with the trailer coupler. Additionally, the method includes receiving vehicle sensor data from one or more vehicle sensors. The method includes determining vehicle motion data based on the received vehicle sensor data. The method also includes determining an updated coupler position based on the trailer coupler position and the vehicle motion data.

Daytime and nighttime stellar sensor with active polarizer

The invention relates to a daytime and nighttime stellar sensor (1), comprising: at least one video camera (2) suitable for taking images of stars (3) in the sky; and a control unit (4), characterized in that it furthermore comprises: a polarizer (5), the control unit (4) being configured: to obtain an estimation of a direction of polarization of the polarized light received from the sky by the video camera (2); and to control the orientation of the polarizer (5) so that said polarizer (5) filters polarized light from the sky directed toward the video camera (2) and having said polarization direction.

Indoor/outdoor detection using a wearable computer

Embodiments are disclosed for indoor/outdoor detection using a mobile device, such as wearable computer (e.g., smartwatch). In an embodiment, a method comprises: receiving, by one or more processors of a wearable computer, wireless access point (AP) scan data, global navigation satellite system (GNSS) data and inertial sensor data; determining, by the one or more processors, a first state of the wearable computer based on the wireless AP scan data; determining, by the one or more processors, a second state of the wearable computer based on a comparison of the GNSS data and the inertial sensor data; and outputting, by the one or more processors, an indoor/outdoor signal indicating that the wearable computer is indoors or outdoors based on the first and second states.

Device and method for analyzing objects

A device and a method for analyzing objects, including buildings, build environments and/or environment areas is proposed. Image data points of an object are gathered and geo-referenced in order to generate object data points. Properties of the object such as material composition, material state or material properties are determined based spectral characteristics evaluation. Three-dimensional object models are generated in accordance with the evaluation of spectral characteristics.

Position estimation device and position estimation method

Provided is a device including an acquisition unit that acquires information indicating a position estimation system selected from among a plurality of position estimation systems for estimating a position of a flight vehicle, and a position estimation unit that estimates the position of the flight vehicle from first information generated by using an inertial sensor of the flight vehicle and second information generated through the position estimation system based on a parameter for the position estimation system.

Systems and methods for identifying landmarks

Systems and methods are disclosed for identifying landmarks. A method for identifying a landmark may include initiating identification of a landmark based on one or more images from a camera, for use in autonomous vehicle navigation, the landmark including a traffic sign; initiating updating a road model with a location of the landmark; and initiating distribution of the road model with the location of the traffic sign to a plurality of autonomous vehicles.

Navigation Method, Navigation Apparatus, Electronic Device, and Storage Medium

A navigation method and a navigation apparatus are provided. The method includes: determining a location area based on an electronic fence and location coordinates; in response to the location area being a transition area between indoors and outdoors, using a visual positioning algorithm to determine a starting point of motion and using a visual-inertial odometry to collect inertial motion information; and generating augmented reality navigation for the motion in the transition area, based on the starting point of the motion and the inertial motion information. 1. A navigation method , comprising:determining a location area based on an electronic fence and location coordinates;in response to the location area being a transition area between indoors and outdoors, using a visual positioning algorithm to determine a starting point of motion and using a visual-inertial odometry to collect inertial motion information; andgenerating augmented reality navigation for the motion in the transition area, based on the starting point of the motion and the inertial motion information.2. The method according to claim 1 , wherein using the visual positioning algorithm to determine the starting point of motion and using the visual-inertial odometry to collect inertial motion information claim 1 , comprises:acquiring a real scene image photographed in the transition area;using the visual positioning algorithm to determine the starting point of the motion in the transition area corresponding to the real scene image; andcollecting the inertial motion information moving from the starting point of the motion to a current location according to the visual-inertial odometry.3. The method according to claim 1 , further comprising:in response to the location area being an outdoor area, using GPS information as basic positioning data; andgenerating augmented reality navigation corresponding to the outdoor area, based on the basic positioning data and a plurality of inertial data collected by ...

REDUCING STARTUP TIME OF AUGMENTED REALITY EXPERIENCE

A method for improving the startup time of a six-degrees of freedom tracking system is described. An augmented reality system receives a device initialization request and activates a first set of sensors in response to the device initialization request. The augmented reality system receives first tracking data from the first set of sensors. The augmented reality system receives an augmented reality experience request and in response to the augmented reality request, causes display of a set of augmented reality content items based on the first tracking data and simultaneously activates a second set of sensors. The augmented reality system receives second tracking data from the activated second set of sensors. The augmented reality system updates the display of the set of augmented reality content items based on the second tracking data.

TRACKING IN A MOVING PLATFORM

A method of tracking 3D position and orientation of an entity in a moving platform is described. The method comprises receiving data sensed by an inertial measurement unit mounted on the entity. Visual tracking data is also received, computed from images depicting the moving platform or the entity in the moving platform. The method computes the 3D position and orientation of the entity by estimating a plurality of states using the visual tracking data and the data sensed by the inertial measurement unit, where the states comprise both states of the moving platform and states of the entity. 1. A method of tracking three-dimensional (3D) position and orientation of an entity in a moving platform , the method comprising:receiving data sensed by an inertial measurement unit mounted on the entity;receiving visual tracking data computed from images depicting the moving platform or the entity in the moving platform; andcomputing the 3D position and orientation of the entity by estimating a plurality of states using the visual tracking data and the data sensed by the inertial measurement unit, where the states comprise both states of the moving platform and states of the entity.2. The method of where the states of the moving platform comprise one or more of: platform angular acceleration claim 1 , platform linear acceleration claim 1 , platform angular velocity claim 1 , platform rotation in a current coordinate frame used by a visual tracker.3. The method of comprising using the computed 3D position and orientation of the entity to do one or more of: place a hologram in a field of view of the entity such that the hologram appears locked to the moving platform claim 1 , control movement of the entity in the moving platform.4. The method of wherein computing the 3D position and orientation of the entity comprises using state propagation and update equations which take into account second order effects.5. The method of comprising receiving data sensed by a second inertial ...

Method and apparatus for depth-aided visual inertial odometry

A method and an apparatus are provided for performing visual inertial odometry (VIO). Measurements are processed from an inertial measurement unit (IMU), a camera, and a depth sensor. Keyframe residue including at least depth residue is determined based on the processed measurements. A sliding window graph is generated and optimized based on factors derived from the keyframe residue. An object pose is estimated based on the optimized sliding window graph.

Method and Apparatus for Scale Calibration and Optimization of a Monocular Visual-Inertial Localization System

The method and system disclosed herein presents a method and system for capturing, by a camera disposed on a device moving in an environment, a plurality of image frames recorded in a first coordinate reference frame at respective locations within a portion of the environment in a first time period; capturing, by an inertial measurement unit disposed on the device, sets of inertial odometry data recorded in a second coordinate reference frame; determining a rotational transformation matrix that corresponds to a relative rotation between the first reference frame and the second reference frame; and determining a scale factor from the matching pairs of image frames. The rotational transformation matrix defines an orientation of the device, and the scale factor and the rotational transformation matrix calibrate the plurality of image frames captured by the camera. 1. A method , comprising:capturing, by a camera disposed on a device moving in an environment, a plurality of image frames recorded in a first coordinate reference frame at respective locations within a portion of the environment in a first time period;capturing, by an inertial measurement unit disposed on the device, sets of inertial odometry data recorded in a second coordinate reference frame, the sets of inertial odometry data corresponding to the plurality of image frames at the respective locations, in the first time period;storing in a buffer, a matching pair of an image frame and a set of inertial odometry data that satisfies first criteria; determining a rotational transformation matrix that corresponds to a relative rotation between the first reference frame and the second reference frame; and', 'determining a scale factor from the matching pairs of image frames, wherein the rotational transformation matrix defines an orientation of the device, and the scale factor and the rotational transformation matrix calibrate the plurality of image frames captured by the camera., 'in accordance with a ...

具有实时在线自我运动估计的激光扫描仪

一种测绘系统，包括：惯性测量单元；摄像机单元；激光扫描单元；以及与惯性测量单元、摄像机单元和激光扫描单元进行通信的计算系统，其中计算系统基于来自惯性测量单元的惯性测量数据以第一频率来计算第一测量预测、基于第一测量预测和来自摄像机单元的视觉测量数据以第二频率来计算第二测量预测、以及基于第二测量预测和来自激光扫描单元的激光测距数据以第三频率来计算第三测量预测。

Self-position calculation device and self-position calculation method