Robot dynamic obstacle avoidance method based on multimodal spiking neural network
US12346112B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 27, 2023 |
| Grant date | Jul 1, 2025 |
| Priority date | — |
| Expiry date | Mar 20, 2044 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02T10/40
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
The present invention provides a robot dynamic obstacle avoidance method based on a multimodal spiking neural network. The present invention realizes a robot obstacle avoidance method in a dynamic environment by fusing laser radar data and processed event camera data and combining with the intrinsic learnable threshold of the spiking neural network for a scenario comprising dynamic obstacles. It solves the difficulty of failure of obstacle avoidance due to the difficulty in perceiving the dynamic obstacles in the obstacle avoidance task of a robot. The present invention helps the robot to fully perceive the static information and the dynamic information of the environment, uses the learnable threshold mechanism of the spiking neural network for efficient reinforcement learning training and decision making, and realizes autonomous navigation and obstacle avoidance in the dynamic environment. An event data enhanced model is combined to better adapt to the dynamic environment for obstacle avoidance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.