Nvidia Corporation

Xiaqing Wu

Mark Damon Wheeler

Lin Yang

According to an aspect of an embodiment, a method may include obtaining multiple sets of camera images and light detection and ranging (LIDAR) point clouds along a track within a geographic sector of a map. The method may include applying a learning model to the camera images to characterize objects within the camera images within classes of objects to generate segmented images. The method may additionally include mapping the sets of camera images and the LIDAR point clouds to three dimensional points of the geographic sector of the map. The method may also include projecting the three dimensional points onto the segmented images to obtain corresponding classes for the three dimensional points of the geographic sector of the map.

Annotating high definition map data with semantic labels

An online system builds a high definition (HD) map for a geographical region based on sensor data captured by a plurality of autonomous vehicles driving through a geographical region. The autonomous vehicles detect map discrepancies based on differences in the surroundings observed using sensor data compared to the high definition map and send messages describing these map discrepancies to the online system. The online system updates existing occupancy maps to improve the accuracy of the occupancy maps (OMaps), and to thereby improve passenger and pedestrian safety. While vehicles are in motion, they can continuously collect data about their surroundings. When new data is available from the various vehicles within a fleet, this can be updated in a local representation of the occupancy map and can be passed to the online HD map system (e.g., in the cloud) for updating the master occupancy map shared by all of the vehicles.

Growing community of inventors

Foster City, CA, United States of America

Xiaqing Wu