Crack avoidance path planning design based on an improved A* algorithm
Abstract
To address the issues of low search efficiency and path irregularity in complex fracture environments, this study proposes a crack avoidance path planning method based on an improved A* algorithm. During the environment modeling phase, a crack buffer zone is introduced and a cost function is constructed. In the search phase, a heuristic function incorporating a crack penalty term is employed to enhance sensitivity to crack distribution. During path generation, Bézier curves are utilized for smoothing. Experimental results in both 2D and 3D environments demonstrate that this method outperforms traditional algorithms in crack avoidance capability, path smoothness, and computational efficiency, providing a viable technical solution for safe path planning in fractured scenarios.
Fields of Study & Subjects
Robotic Path Planning Algorithms
Reinforcement Learning in Robotics
Metaheuristic Optimization Algorithms Research
Publication details
- Journal / source
- International Conference on Computer Vision, Pattern Recognition, and Detection (ICVPRD)
- Pages
- 23–23
- Publication date
- 5 March 2026
- Language
- EN