An Improved Flyod-Weighted Jump Point Search Algorithm in Mobile Path Planning
Hao Zhang, Yixin Zhao · 2023
The search-based path planning algorithm encounters several issues, such as time-consuming calculations and redundant path nodes during mobile robot path finding. This paper aims to optimize the heuristic function by utilizing the jump search algorithm and an adaptive dynamic weight. This optimization significantly accelerates the search speed of the algorithm. Additionally, the Floyd algorithm is employed to p rune redundant intermediate nodes, effectively reducing inflection points. Comparing the newly proposed F-WJPS algorithm with the A* and JPS algorithms, we observe a reduction in solution time by 95.29% and 46.82% respectively. Furthermore, the F-WJPS algorithm achieves a path length reduction of 6.2% and 6.1% respectively. Moreover, the number of inflection points in the path is decreased, making it more suitable for path planning in mobile robots. Additionally, this paper addresses the issue of collision between the F-WJPS algorithm-generated path and obstacles. By considering the constraint of a safe corridor, we solve the final Bessel curve trajectory, effectively avoiding collision risks and ensuring a smoother trajectory.