Computer-implemented automatic annotation of a LiDAR point cloud

A computer-implemented method comprising:

• receiving LiDAR data for an airport environment, wherein the LiDAR data includes a LiDAR point cloud including a plurality of points in the airport environment;
• segmenting the LiDAR point cloud into a ground region and a non-ground region;
• automatically clustering, via a trained machine learning model, different points in the non-ground region into a plurality of non-ground segments;
• automatically labeling, via the trained machine learning model, the plurality of non-ground segments with classification labels selected from an airport domain, wherein the classification labels include dynamic semantic labels for movable objects and non-dynamic semantic labels for fixed objects;
• and
• outputting a labeled LiDAR point cloud including the plurality of non-ground segments labeled with respective classification labels and the points in the ground region.

A computing device, comprising:

• one or more processors configured to execute instructions stored in memory to:
• receive laser imaging detection and ranging (LiDAR) data for an airport environment, wherein the LiDAR data includes a LiDAR point cloud including a plurality of points in the airport environment;
• segment the LiDAR point cloud into a ground region and a non-ground region;
• automatically cluster, via a trained machine learning model, different points in the non-ground region into a plurality of non-ground segments;
• automatically annotate, via the trained machine learning model, the plurality of non-ground segments with classification labels selected from an airport domain;
• output a labeled LiDAR point cloud including the plurality of non-ground segments labeled with respective classification labels and the points in the ground region;
• receive one or more images of the airport environment captured by one or more cameras;
• and
• automatically annotate a plurality of objects in the one or more images with classification labels corresponding to the plurality of non-ground segments in the labeled LiDAR point cloud.