Point cloud filtering with semantic segmentation

Abstract

Techniques are disclosed for filtering point cloud data associated with particulate matter (e.g., gas, exhaust, fog, etc.) which do not impact driving from data used to plan a trajectory and/or a route of a robotic platform. The filtering may be based on determining that a set of points associated with a point cloud represents a navigable space for the robotic platform. The point cloud data may be filtered based on a determination that one or more safety conditions are satisfied. Semantic segmentation may be performed on an image to determine pixel classification probability distributions associated with pixels of the image. Data associated with the set of points may be projected onto the image to identify corresponding pixels. Confidence scores associated with pixel classification probability distributions for the identified pixels may be queried. A classification probability distribution for the set of points may be determined based at least in part on the queried confidence scores.