Path Planning of Robot Based on Improved Artificial Potentional Field Method

摘要

Aiming at the problem of path planning failure in traditional artificial potential field method, we analyze the reason why target near the obstacles is unreachable and how to avoid the local minimum point during the path planning. Considering kinematic characteristics of the robot, an improved path planning algorithm based on improved artificial potential field method is proposed in this paper. Firstly, this algorithm introduces the concept of minimum safe distance and relative distance between the robot and the target, and adopts Gaussian transformation method to optimize the traditional potential function to solve the problem that the target near the obstacles is not reachable. Secondly, the evaluation criteria of the local minimum points are set up. The problem of local minima is solved by the gravitational field rotation and the virtual obstacle filling strategy. Finally, the simulation result of MATALB proves validity and feasibility of this method.