US 10,769,840 B2 · Analysis of point cloud data using polar depth maps and planarization techniques

Abstract

Various types of systems or technologies can be used to collect data in a 3D space. For example, LiDAR (light detection and ranging) and RADAR (radio detection and ranging) systems are commonly used to generate point cloud data for 3D space around vehicles, for such functions as localization, mapping, and tracking. This disclosure provides improvements for processing the point cloud data that has been collected. The processing improvements include using a three dimensional polar depth map to assist in performing nearest neighbor analysis on point cloud data for object detection, trajectory detection, freespace detection, obstacle detection, landmark detection, and providing other geometric space parameters.

Claims24

Dependent claims

A method of generating geometric space parameters, utilizing a graphics processing unit (GPU), comprising:

transforming point cloud data, for a three dimensional (3D) point representation, to a 3D polar depth map that includes distances between data points of said point cloud data and a sensor for collecting said data points, wherein said point cloud data are not received as said polar depth map;
determining plane information for said data points of said polar depth map;
performing nearest neighbor analysis for said data points utilizing said plane information and said polar depth map;
and
generating said geometric space parameters utilizing said nearest neighbor analysis and said polar depth map.

2 more elements

Dependencies are inferred from the claim text.

Analysis of point cloud data using polar depth maps and planarization techniques

Life of this patent

Analysis of point cloud data using polar depth maps and planarization techniques

Life of this patent

Abstract

Claims24