Abstract: A method comprises: determining that a vehicle is at a first location; controlling motion of the vehicle using an advanced driver assistance system (ADAS); determining a second location for the vehicle based on lane sensing information of a lane monitoring system of the vehicle and a first travel distance of the vehicle since the first location, the lane sensing information reflecting a lane curvature; determining a third location for the vehicle based on a heading angle of the vehicle and a second travel distance of the vehicle since the first location; determining a fourth location for the vehicle by fusing the second and third locations with each other; and controlling the motion of the vehicle using the ADAS based on the fourth location.

Abstract: A method comprises: determining that a vehicle is at a first location; controlling motion of the vehicle using an advanced driver assistance system (ADAS); determining a second location for the vehicle based on receiving a first sensor return indicating at least a first static object and a second static object; determining a third location for the vehicle based on a heading angle of the vehicle and a first travel distance of the vehicle since the first location; determining a fourth location for the vehicle by fusing the second and third locations with each other, and controlling the motion of the vehicle using the ADAS based on the fourth location.

Abstract: A method comprises: determining that a vehicle is at a first location; controlling motion of the vehicle using an advanced driver assistance system (ADAS); determining a second location for the vehicle based on receiving a first sensor return indicating at least a first static object and a second static object, and based on a first travel distance of the vehicle since the first location; determining a third location for the vehicle based on lane sensing information of a lane monitoring system of the vehicle and a second travel distance of the vehicle since the first location, the lane sensing information reflecting a vehicle curvature; determining a fourth location for the vehicle by fusing the second and third locations with each other; and controlling the motion of the vehicle using the ADAS based on the fourth location.

Abstract: In one embodiment, a method includes accessing a set of data points captured using a radar system of the vehicle. Each data point is associated with at least three measurements include a Doppler measurement, a range measurement, and an azimuth measurement in reference to the radar system. The method also includes clustering the set of data points into one or more first clusters based on a first pair of the three measurements associated with each of the data points; and clustering the set of data points into one or more second clusters based on a second pair of the three measurements associated with each of the data points. The second pair being different from the first pair of the three measurements.

Abstract: Systems, methods, and non-transitory computer-readable media provide an adaptive gating mechanism for radar tracking initialization. Specifically, the radar system obtains measurement data of target points, and then determines, based on the measured position and dopplers of points in the first few scans, whether the doppler and displacement parameters satisfy an initialization constraint. When the initialization constraint is not satisfied, the radar system flags the respective cluster with an initialization flag, and adaptively uses the measured position and doppler of scanned points to determine the gating size for the next scan, instead of using a fixed gate size. When the initialization flag of the same cluster across a few consecutive scans satisfies a combination logic, the radar system determines that the tracking enters into the association stage, e.g., the radar system formally generates a track for the target points along a series of scans.

Abstract: Systems, methods, and non-transitory computer-readable media provide a blind online calibration mechanism to calibrate the position of the radar unit while the self-driving vehicle is in motion without the use of any map data. Specifically, a calibration system associated with the self-driving vehicle is configured to adjust the boresight angle of the radar within a calibration range and monitor the convergence or divergence pattern of the resulting clutter locations. The boresight angle of the radar unit may be progressively adjusted in static or dynamic degree increments until the convergence of the clutter curves is observed. In this way, without using any map data or factory settings, radar calibration can be conducted as often as needed while the vehicle is moving. Radar sensing and measurement accuracy is thus improved.

Abstract: Various embodiments of the present technology can include systems, methods, and non-transitory computer readable media configured to adaptively identify clutter points representing static objects from a sensor data scan. A plurality of sensor data scans are captured, by a sensor unit placed on a vehicle, at a plurality of consecutive time instants while the vehicle is traveling along a route. A set of target points from each of the plurality of sensor data scans is identified. A characteristic indicative of a trajectory pattern relating to one or more respective sets of target points is obtained from one or more sensor data scans taken at consecutive time instants. In response to determining that the characteristic satisfies a pre-defined condition, an indicator with the respective sets of target points is adopted as relating to one or more static objects in an environment at which the vehicle is situated.

Abstract: In one embodiment, a method includes accessing a set of data points captured using a radar system of the vehicle. Each data point is associated with at least three measurements include a Doppler measurement, a range measurement, and an azimuth measurement in reference to the radar system. The method also includes clustering the set of data points into one or more first clusters based on a first pair of the three measurements associated with each of the data points; and clustering the set of data points into one or more second clusters based on a second pair of the three measurements associated with each of the data points. The second pair being different from the first pair of the three measurements.

Abstract: Various embodiments of the present technology can include systems, methods, and non-transitory computer readable media configured to adaptively identify clutter points representing static objects from a sensor data scan. A plurality of sensor data scans are captured, by a sensor unit placed on a vehicle, at a plurality of consecutive time instants while the vehicle is traveling along a route. A set of target points from each of the plurality of sensor data scans is identified. A characteristic indicative of a trajectory pattern relating to one or more respective sets of target points is obtained from one or more sensor data scans taken at consecutive time instants. In response to determining that the characteristic satisfies a pre-defined condition, an indicator with the respective sets of target points is adopted as relating to one or more static objects in an environment at which the vehicle is situated.

Abstract: Systems, methods, and non-transitory computer-readable media provide an adaptive gating mechanism for radar tracking initialization. Specifically, the radar system obtains measurement data of target points, and then determines, based on the measured position and dopplers of points in the first few scans, whether the doppler and displacement parameters satisfy an initialization constraint. When the initialization constraint is not satisfied, the radar system flags the respective cluster with an initialization flag, and adaptively uses the measured position and doppler of scanned points to determine the gating size for the next scan, instead of using a fixed gate size. When the initialization flag of the same cluster across a few consecutive scans satisfies a combination logic, the radar system determines that the tracking enters into the association stage, e.g., the radar system formally generates a track for the target points along a series of scans.

Abstract: Systems, methods, and non-transitory computer-readable media provide a blind online calibration mechanism to calibrate the position of the radar unit while the self-driving vehicle is in motion without the use of any map data. Specifically, a calibration system associated with the self-driving vehicle is configured to adjust the boresight angle of the radar within a calibration range and monitor the convergence or divergence pattern of the resulting clutter locations. The boresight angle of the radar unit may be progressively adjusted in static or dynamic degree increments until the convergence of the clutter curves is observed. In this way, without using any map data or factory settings, radar calibration can be conducted as often as needed while the vehicle is moving. Radar sensing and measurement accuracy is thus improved.

Abstract: A system for generating a ground truth dataset for motion planning is disclosed. The system includes: a collecting module configured to collect LiDAR scans; a detecting module configured to detect two pose estimates that are closest to LiDAR scan accusation time; a determining module configured to determine LiDAR's poses based on an interpolation; and a transforming module configured to transform LiDAR raw scans into undistorted LiDAR scans.

Abstract: A system for generating a ground truth dataset for motion planning is disclosed. The system includes: a collecting module configured to collect LiDAR scans; a detecting module configured to detect two pose estimates that are closest to LiDAR scan accusation time; a determining module configured to determine LiDAR's poses based on an interpolation; and a transforming module configured to transform LiDAR raw scans into undistorted LiDAR scans.