System and method for motion prediction in autonomous driving
US12340520B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 20, 2022 |
| Grant date | Jun 24, 2025 |
| Priority date | — |
| Expiry date | Aug 24, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30252
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure provides a system and a method for motion prediction for autonomous driving. The system disclosed herein provides an efficient deep-neural-network-based system to jointly perform perception and motion prediction from 3D point clouds. This system is able to take a pair of LiDAR sweeps as input and outputs for each point in the second sweep, both a classification of the point into one of a set of semantic classes, and a motion vector indicating the motion of the point within the world coordinate system. The system includes a spatiotemporal pyramid network, which extracts deep spatial and temporal features in a hierarchical fashion. The training of this system is regularized with spatial and temporal consistency losses. Thus providing an improved motion planner for autonomous driving applications.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.