Deep learning-based feature extraction for LiDAR localization of autonomous driving vehicles
US11594011B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Jan 30, 2019 |
| Grant date | Feb 28, 2023 |
| Priority date | — |
| Expiry date | Nov 23, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30252
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a method for extracting point cloud features for use in localizing an autonomous driving vehicle (ADV) includes selecting a first set of keypoints from an online point cloud, the online point cloud generated by a LiDAR device on the ADV for a predicted pose of the ADV; and extracting a first set of feature descriptors from the first set of keypoints using a feature learning neural network running on the ADV, The method further includes locating a second set of keypoints on a pre-built point cloud map, each keypoint of the second set of keypoints corresponding to a keypoint of the first set of keypoint; extracting a second set of feature descriptors from the pre-built point cloud map; and estimating a position and orientation of the ADV based on the first set of feature descriptors, the second set of feature descriptors, and a predicted pose of the ADV.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.