Global Dynamic Path Planning Fusion Algorithm Combining Jump-A* Algorithm and Dynamic Window Approach

Abstract

In order to meet the performance requirements of global optimality and path smoothness in robot path planning, a new fusion algorithm of jump-A^* algorithm and dynamic window approach is proposed. First, A^* algorithm is optimized by using the jump point search method and a new distance evaluation function defined by Manhattan and Euclidean distance to obtain global path information. Then take the dynamic window approach as the core by integrating the global path information to safely plan a global optimal path with high smoothness. The experimental results show that the new fusion algorithm proposed in this paper can not only effectively solve the problem of non-continuous curvature and excessive turning angle at the turning points of the path planned by jump-A^* algorithm, but also improve the smoothness of the path and the global optimality. This research is beneficial to the motion control of robots and has certain reference for robot navigation.