Robot Path Planning Algorithm based on Bi-RRT and Potential Field

Abstract

To improve the search probability and search efficiency, the path planning method combining Bi-RRT and improved potential field is proposed. By introducing the resultant force of the improved potential field as the heuristic information of random tree expansion and changing the target point of the bidirectional random expansion trees, the gradient descent method and the target sampling method were adopted to enable the bidirectional random expansion tree to rapidly grow to the target point, avoiding the random tree from exploring useless areas, which improved the path searching ability and planning efficiency. Matlab software was used to simulate the algorithm, RRT-connect algorithm and artificial potential field method in different environments. The simulation results verified the effectiveness and superiority of the hybrid algorithm.