SYSTEM AND METHOD FOR THE SEGMENTATION OF OPTICAL COHERENCE TOMOGRAPHY SLICES

The present disclosure describes a system and method to segment optical coherence tomography (OCT) images. The present system uses a hybrid method that employs both Bayesian level sets (BLS) and graph-based segmentation algorithms. The system first identifies retinal tissue within an OCT image using the BLS algorithms. The identified retinal tissue is then further segmented using the graph-based segmentation algorithms.

SYSTEM AND METHOD FOR THE SELECTION OF OPTICAL COHERENCE TOMOGRAPHY SLICES

The present disclosure describes systems and methods to select fovea containing optical coherence tomography (OCT) images. The systems and methods described herein receive a plurality of OCT images. The portion of the OCT images are selected for further processing, where a line tracing the border between the retina and non-retina tissue is generated. A difference of the line is generated. Candidate OCT images are then generated responsive to the generated difference line. The lowest point among each difference lines generated for each of the OCT images is identified, and the OCT image to which the lowest point corresponds is identified as the fovea containing OCT image.

SYSTEM AND METHOD FOR WAVELET-BASED GAIT CLASSIFICATION

A motion classification system comprises an inertial measurement unit configured to sense motion of a user and to output one or more channels of inertial motion data corresponding to the sensed motion; and a processing unit configured to calculate a coefficient vector for each of the one or more channels based on a wavelet transformation of the respective inertial motion data, and to select one of a plurality of gaits as the user's gait based on the calculated coefficient vector of at least one of the one or more channels and on a plurality of templates, each template corresponding to one of the plurality of gaits. 1. A motion classification system comprising:an inertial measurement unit configured to sense motion of a user and to output one or more channels of inertial motion data corresponding to the sensed motion; anda processing unit configured to calculate a coefficient vector for each of the one or more channels based on a wavelet transformation of the respective inertial motion data, and to select one of a plurality of gaits as the user's gait based on the calculated coefficient vector of at least one of the one or more channels and on a plurality of templates, each template corresponding to one of the plurality of gaits.2. The motion classification system of claim 1 , wherein the processing unit is further configured to calculate a distance-traveled estimate based claim 1 , in part claim 1 , on the selected gait;wherein the processing unit is configured to update a navigation solution based on the distance-traveled estimate.3. The motion classification system of claim 2 , wherein the motion classification system further comprises:one or more aiding sensors each configured to sense motion of the user and output signals corresponding to the user's motion;wherein the processing unit is further configured to update the navigation solution based on the signals from the one or more aiding sensors.4. The motion classification system of claim 1 , wherein claim 1 , ...

COLLABORATIVE NAVIGATION USING CONDITIONAL UPDATES

A method for collaborative navigation between two or more platforms is provided. The method comprises establishing a communication link between a first platform and a second platform, making a sensor measurement from the first platform, updating state and covariance elements of the first platform, and transmitting the updated state and covariance elements from the first platform to the second platform. A conditional update is performed on the second platform to compute a new estimate of state and covariance elements on the second platform, which takes into account the measurement from the first platform. The method further comprises making a sensor measurement from the second platform, updating state and covariance elements of the second platform, and transmitting the updated state and covariance elements from the second platform to the first platform. A conditional update is performed on the first platform to compute a new estimate of state and covariance elements on the first platform, which takes into account the measurement from the second platform. 1. A method for collaborative navigation between two or more platforms , the method comprising:establishing a communication link between a first platform and a second platform;making a sensor measurement from the first platform;updating state and covariance elements of the first platform;transmitting the updated state and covariance elements from the first platform to the second platform;performing a conditional update on the second platform to compute a new estimate of state and covariance elements on the second platform, which takes into account the measurement from the first platform;making a sensor measurement from the second platform;updating state and covariance elements of the second platform;transmitting the updated state and covariance elements from the second platform to the first platform; andperforming a conditional update on the first platform to compute a new estimate of state and covariance elements on ...

AUTONOMOUS VEHICLE: VEHICLE LOCALIZATION

In an embodiment, a localization module can provide coordinates of the vehicle relative to the Earth and relative to the drivable surface, both of which are precise enough to allow for self-driving, and further can compensate for a temporary lapse in reliable GPS service by continuing to track the car's position by tracking its movement with inertial sensors (e.g., accelerometers and gyroscopes) and RADAR data. The localization module bases its output on a geolocation relative to the Earth and sensor measurements of the drivable surface and its surroundings to determine where the car is in relation to the Earth and the drivable surface. 1. A method of navigating an autonomous vehicle , the method comprising:correlating a global positioning system (GPS) signal received at an autonomous vehicle with a position on a map loaded from a database;determining, from a list of features received from a RADAR sensor of the autonomous vehicle over a plurality of time steps relative to the autonomous vehicle, a location of the autonomous vehicle relative to the drivable surface; andproviding an improved location of the autonomous vehicle based on the location of the autonomous vehicle relative to the drivable surface and the GPS signal by correlating the location of the autonomous vehicle relative to the drivable surface to lane data and drivable surface width from a map.2. The method of claim 1 , further comprising determining claim 1 , from the list of features claim 1 , an attitude of the autonomous vehicle relative to the drivable surface.3. The method of claim 1 , further comprising matching image data received by a vision sensor of the autonomous vehicle to landmark features stored in a database.4. The method of claim 1 , further comprising:tracking relative position of each feature from a given sensor across multiple time steps; andretaining features determined to be stationary based on the tracked relative position.5. The method of claim 4 , further comprising:for radar ...

Autonomous vehicle localization

In an embodiment, a localization module can provide coordinates of the vehicle relative to the Earth and relative to the drivable surface, both of which are precise enough to allow for self-driving, and further can compensate for a temporary lapse in reliable GPS service by continuing to track the car's position by tracking its movement with inertial sensors (e.g., accelerometers and gyroscopes) and RADAR data. The localization module bases its output on a geolocation relative to the Earth and sensor measurements of the drivable surface and its surroundings to determine where the car is in relation to the Earth and the drivable surface.

Collaborative navigation using conditional updates

A method for collaborative navigation between two or more platforms is provided. The method comprises establishing a communication link between a first platform and a second platform, making a sensor measurement from the first platform, updating state and covariance elements of the first platform, and transmitting the updated state and covariance elements from the first platform to the second platform. A conditional update is performed on the second platform to compute a new estimate of state and covariance elements on the second platform, which takes into account the measurement from the first platform. The method further comprises making a sensor measurement from the second platform, updating state and covariance elements of the second platform, and transmitting the updated state and covariance elements from the second platform to the first platform. A conditional update is performed on the first platform to compute a new estimate of state and covariance elements on the first platform, which takes into account the measurement from the second platform.

Autonomous vehicle: vehicle localization

In an embodiment, a localization module can provide coordinates of the vehicle relative to the Earth and relative to the drivable surface, both of which are precise enough to allow for self-driving, and further can compensate for a temporary lapse in reliable GPS service by continuing to track the car's position by tracking its movement with inertial sensors (e.g., accelerometers and gyroscopes) and RADAR data. The localization module bases its output on a geolocation relative to the Earth and sensor measurements of the drivable surface and its surroundings to determine where the car is in relation to the Earth and the drivable surface.

System and method for the segmentation of optical coherence tomography slices

The present disclosure describes a system and method to segment optical coherence tomography (OCT) images. The present system uses a hybrid method that employs both Bayesian level sets (BLS) and graph-based segmentation algorithms. The system first identifies retinal tissue within an OCT image using the BLS algorithms. The identified retinal tissue is then further segmented using the graph-based segmentation algorithms.

System and method for the segmentation of optical coherence tomography slices

The present disclosure describes a system and method to segment optical coherence tomography (OCT) images. The present system uses a hybrid method that employs both Bayesian level sets (BLS) and graph-based segmentation algorithms. The system first identifies retinal tissue within an OCT image using the BLS algorithms. The identified retinal tissue is then further segmented using the graph-based segmentation algorithms.

Navigationsverfahren und -system unter verwendung von geländemerkmalen

System and method for the selection of optical coherence tomography slices

The present disclosure describes systems and methods to select fovea containing optical coherence tomography (OCT) images. The systems and methods described herein receive a plurality of OCT images. The portion of the OCT images are selected for further processing, where a line tracing the border between the retina and non-retina tissue is generated. A difference of the line is generated. Candidate OCT images are then generated responsive to the generated difference line. The lowest point among each difference lines generated for each of the OCT images is identified, and the OCT image to which the lowest point corresponds is identified as the fovea containing OCT image.

System and method for the segmentation of optical coherence tomography slices