Abstract: An autonomous vehicle is disclosed that includes a velocity sensor; a radar system; a digital storage medium; and a controller in communication with the digital storage medium, radar system, and the velocity sensor. The controller, for example, may retrieve map data from the digital storage medium; receive current radar data from the radar system; receive autonomous vehicle velocity data from the velocity sensor; identify radar data points in the current radar data that represent objects in motion; remove radar data points from the current radar data that represent objects in motion; and/or match the radar data with the map data to return location data.

Abstract: An autonomous vehicle is disclosed that includes a velocity sensor; a radar system; a digital storage medium; and a controller in communication with the digital storage medium, radar system, and the velocity sensor. The controller, for example, may retrieve map data from the digital storage medium; receive current radar data from the radar system; receive autonomous vehicle velocity data from the velocity sensor; identify radar data points in the current radar data that represent objects in motion; remove radar data points from the current radar data that represent objects in motion; and/or match the radar data with the map data to return location data.

Abstract: A UAS may use camera-captured ground feature data to iteratively estimate pose change through a Kalman filter. To avoid excessive drift, the UAS may periodically perform a reset by publishing delta pose and covariance as an edge in a global pose graph, by zeroing out the delta pose and covariance. To further improve global pose estimation, two UASs may share range information and associated pose graph information, thereby providing an additional constraint for each UAS to use in its pose graph optimization.