A fusion path planning method for mobile robots based on Voronoi skeleton
By converting the raster map into a skeleton map and combining the global boot-based DWA algorithm, the problems of many path inflection points, unsmooth operation, and unsecurity in path planning are solved, and a smoother, safer and more efficient path planning is achieved.
CN118915716BActive Publication Date: 2025-03-25NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Patent Information
- Application Number
- CN202410874638.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-02
- Publication Date
- 2025-03-25
- Estimated Expiration
- 2044-07-02
AI Technical Summary
Technical Problem
In the prior art, path planning under grid maps, there are problems such as many path inflection points, unsmooth operation, and unsecurity.
Method used
By converting the environment raster map into a skeleton map, a globally optimized prior path is generated based on the skeleton map, and real-time local planning is performed in combination with the global bootstrap DWA algorithm.
Benefits of technology
Reduces the path length and number of inflection points, making the robot's running path smoother and safer, and improves navigation efficiency and the use of global paths.
✦ Generated by Eureka AI based on patent content.
Abstract
The present invention relates to a mobile robot path planning method based on Voronoi skeleton, and belongs to the field of path planning. First, a laser mapping radar is used to construct a grid map of the working environment of the mobile robot, and a grid-skeleton graph construction method is used to sequentially use Delaunay triangulation, dual Voronoi graph construction and undirected graph adjacency matrix transformation multiple steps to construct a Voronoi skeleton graph of the working environment. Secondly, the A* algorithm is used to perform global path planning based on the skeleton vertices, and the path points are optimized according to the spatial obstacle avoidance requirements to generate a global optimization prior path. After that, the DWA algorithm speed sampling space is optimized, and the global optimization guidance is introduced by improving the evaluation function to construct a global guided DWA algorithm. Finally, the local path planning is integrated with the global planning path through the dynamic target point, and the surrounding obstacles are detected in real time to perform obstacle avoidance operations until the mobile robot reaches the end point. The present invention significantly improves the navigation safety, path smoothness and operation efficiency of the mobile robot.
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