Adaptive point cloud generation for autonomous vehicles

A vehicle comprising:

• at least one computer processor;
• and
• at least one non-transitory storage medium storing instructions which, when executed by the at least one computer processor, cause the at least one computer processor to:
• receive a plurality of LiDAR points from a LiDAR system of the vehicle, the plurality of LiDAR points representing at least one object in an environment traveled by the vehicle;
• determine a Euclidean distance of each LiDAR point of the plurality of LiDAR points;
• compare the Euclidean distance of each LiDAR point of the plurality of LiDAR points with a respective sampled Euclidean distance from a standard normal distribution of Euclidean distances;
• responsive to the Euclidean distance of each LiDAR point of the plurality of LiDAR points being less than the respective sampled Euclidean distance, remove the LiDAR point from the plurality of LiDAR points to generate a point cloud;
• and
• operate the vehicle based on the point cloud.

At least one non-transitory storage media storing instructions which, when executed by at least one computing device, cause the at least one computing device to:

• receive a plurality of LiDAR points from a LiDAR system of the vehicle, the plurality of LiDAR points representing at least one object in an environment traveled by the vehicle;
• determine a Euclidean distance of each LiDAR point of the plurality of LiDAR points;
• compare the Euclidean distance of each LiDAR point of the plurality of LiDAR points with a respective sampled Euclidean distance from a standard normal distribution of Euclidean distances;
• responsive to the Euclidean distance of each LiDAR point of the plurality of LiDAR points being less than the respective sampled Euclidean distance, remove the LiDAR point from the plurality of LiDAR points to generate a point cloud;
• and
• operate the vehicle based on the point cloud.