Local Path Planning Of Mobile Robot Based On Artificial Potential Field Method

With the rapid development of artificial intelligence,robot technology is becoming more and more mature.Navigation technologies such as locating,path planning and path tracking have become a hot topic in robot research,and path planning algorithm is one of the key technologies.Artificial Potential Field method has been widely used in local path planning algorithms of mobile robots because of its good real-time performance and simple calculation.In the process of the local path planning,the sensor information is incomplete,so the robot is easy to trap into local minimum point and wanders around the trap.This paper is based on Artificial Potential Field method,combining fuzzy control and the Finite State Machine algorithm,to overcome the problems existed in the traditional Artificial Potential Field method,and studies how mobile robots plan out a smooth and shorter path in simple and complex environments.Aiming at the local minimum point problem existed in local path planning of mobile robots based on Artificial Potential Field method,two local minimum point obstacle avoidance strategies for setting virtual target points are proposed: VTP-90 and VTP-120 local minimum point obstacle avoidance strategies.The VTP-90 local minimum obstacle avoidance strategy guides the mobile robot to escape from the local minimum point area by setting the virtual target point at an appropriate position,along the rotation direction of the repulsive force component 90 degrees through the local minimum point environment detection and multiple U-shaped obstacle environment detection.The VTP-120 strategy is to set the virtual target point at the appropriate position of the repulsive force component rotated 120 degrees in the local minimum point environment,so as to realize the obstacle avoidance task in various environments.The two algorithms are verified and compared by simulation on MATLAB platform.The results show that the VTP-120 local minimum point obstacle avoidance strategy is simpler and applicable to more comprehensive obstacle environment.Aiming at the problem that the planned path of mobile robot is too long when the VTP-120 Artificial Potential Field method is used to escape from the local minimum point,the fuzzy potential field method is proposed by combining the VTP-120 Artificial Potential Field method with fuzzy control algorithm.The fuzzy controller is constructed to predict the obstacle environment,and the virtual target points are set at the appropriate positions to avoid obstacles in time.The problem of the long path is solved when the mobile robot plans the path in the complex environment.The Finite State Machine is used to judge the density state of the obstacle environment,the algorithm transformation strategy is set,and the appropriate algorithm is selected for path planning according to the obstacle environment,so that the improved algorithm is applicable to a variety of obstacle environment.The algorithm is verified by simulation on MATLAB platform.The results show that the algorithm can make the robot escape from the local minimum point and shorten the path length.This algorithm is not only suitable for simple and discrete environments,but also can plan the feasible optimal path in difficult environments where the traditional Artificial Potential Field method is difficult to operate,such as wall,U-shaped and multiple U-shaped obstacle environments.