LiDAR localization using 3D CNN network for solution inference in autonomous driving vehicles
US11531110B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Jan 30, 2019 |
| Grant date | Dec 20, 2022 |
| Priority date | — |
| Expiry date | Aug 15, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30252
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a method for solution inference using neural networks in LiDAR localization includes constructing a cost volume in a solution space for a predicted pose of an autonomous driving vehicle (ADV), the cost volume including a number of sub volumes, each sub volume representing a matching cost between a keypoint from an online point cloud and a corresponding keypoint on a pre-built point cloud map. The method further includes regularizing the cost volume using convention neural networks (CNNs) to refine the matching costs; and inferring, from the regularized cost volume, an optimal offset of the predicted pose. The optimal offset can be used to determine a location of the ADV.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.