Abstract: Methods and systems for improving the charging of battery electric vehicles (BEVs) using solar irradiance. For example, a computing system may be configured to obtain sensor data from a plurality of vehicles, where the sensor data is indicative of sensor measurement data acquired by a perception sensor of the respective vehicle, a time the sensor measurement data was acquired, and a pose of the vehicle. The computing system may be configured to, based on the sensor data from the plurality of vehicles, determine a plurality of solar irradiance levels for a plurality of locations within a geographic area. The computing system may be configured to generate a map layer, the map layer being indicative of a respective solar irradiance level for each of the plurality of locations. The computing system may be configured to output the map layer for integration into map data associated with the geographic area.

Abstract: Briefly, example methods, apparatuses, and/or articles of manufacture may be implemented to access, from at least one memory device, sensor measurements generated by one or more sensors mounted in a vehicle and to generate an occupancy grid having grid cells that track occupancy, by static obstacles and dynamic obstacles, in an environment of the vehicle based on the accessed sensor measurements. An apparatus may additionally allocate (i) a first set of particles to estimate occupancy of grid cells by the static obstacles and states of the static obstacles and (ii) a second set of particles to estimate occupancy of grid cells by the dynamic obstacles and states of the dynamic obstacles. An apparatus may additionally execute one or more operations to plan motion of the vehicle based on the estimated occupancy of grid cells by the static obstacles and dynamic obstacles.

Abstract: A vehicle computing system can receive raw sensor data in both a traditional sensor data processing module and a learned sensor data processing module. Each module can reproject sensor data in BEV space, and can optionally perform sensor fusion when multiple sensor data types are processed.

Abstract: Briefly, example methods, apparatuses, and/or articles of manufacture may be implemented to access, from at least one memory device, sensor measurements generated by one or more sensors mounted in a vehicle and to generate an occupancy grid having grid cells that track occupancy, by static obstacles and dynamic obstacles, in an environment of the vehicle based on the accessed sensor measurements. An apparatus may additionally allocate (i) a first set of particles to estimate occupancy of grid cells by the static obstacles and states of the static obstacles and (ii) a second set of particles to estimate occupancy of grid cells by the dynamic obstacles and states of the dynamic obstacles. An apparatus may additionally execute one or more operations to plan motion of the vehicle based on the estimated occupancy of grid cells by the static obstacles and dynamic obstacles.