A RGB point clouds based map generation system for autonomous vehicles

Abstract

In one embodiment, a system receives a number of point clouds captured by one or more LIDAR sensors of an ADV and corresponding poses(1801). The system receives a number of RGB images from one or moreimage capturing sensors of the ADV(1802). The system synchronizes the RGB images with the point clouds to obtain RGB point clouds(1803). The system extracts features from the RGB point clouds, the features including contextual and spatial information of the RGB point clouds(1804). The system registers the RGB point clouds based on the extracted features(1805) and generates a point cloud map basedon the registration of the RGB point clouds(1806).

Description

technical field [0001] Embodiments of the present disclosure generally relate to operating an autonomous vehicle. More specifically, embodiments of the present disclosure relate to an RGB (red, green, blue) point cloud based map generation system for autonomous driving vehicles (ADVs). Background technique [0002] Vehicles operating in an autonomous mode (e.g., driverless) can free passengers (especially the driver) from some driving-related duties. When operating in autonomous mode, the vehicle can navigate to various locations using on-board sensors, allowing the vehicle to operate with minimal human interaction or in some situations without any passengers. [0003] Motion planning and control are key operations in autonomous driving. However, traditional motion planning operations mainly estimate the difficulty of completing a given path based on its curvature and velocity, without considering the characteristic differences of different types of vehicles. The same mot...

AI Technical Summary

Problems solved by technology

The accuracy of HD 3D point cloud maps may be compromised if the point cloud map has ghost images caused by, for example, stitching of point clouds

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