融合视觉语义信息与激光雷达的四足机器人路径规划方法
By integrating visual semantic information with LiDAR path planning methods, the problem of blind spots in perception for quadruped robots in industrial scenarios has been solved, achieving safer and more efficient navigation and obstacle avoidance capabilities.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTHWEST JIAOTONG UNIV
- Filing Date
- 2025-06-06
- Publication Date
- 2026-07-17
AI Technical Summary
In industrial settings such as railway maintenance, the perception system of quadruped robots is unable to accurately identify the location of ditches, causing them to mistakenly enter the ditches and resulting in accidents such as falls and collisions, which affects navigation safety and work efficiency.
A path planning method integrating visual semantic information and LiDAR is proposed. By acquiring key ground semantic information and depth images, it is converted into key ground semantic point cloud information of LiDAR, multi-source point cloud fusion is performed, non-ground interference points are filtered out, a semantically enhanced local path planning model is constructed, and a semantic penalty term is introduced to avoid dangerous areas.
It significantly improves the navigation safety and task execution efficiency of quadruped robots in high-risk industrial environments, and achieves a more stable dynamic obstacle avoidance strategy.
Smart Images
Figure CN120628103B_ABST