移动机器人避障路径规划改进人工势场法

针对路径规划中的大型障碍物,机器人、障碍物与目标点三者一线,以及局部最小值等困难问题,提出了相应的改进人工势场算法。针对大型障碍物问题,采用障碍物边界斥力算法改进传统人工势场斥力函数,确保算法的实用性。针对机器人、障碍物与目标点三者在同一条直线时目标不可达问题,应用虚拟子目标引力算法,确保目标点是机器人的势场全局最小点,使得机器人能顺利到达目标点。针对在障碍物环境下的局部最小值问题,采用区域隔离障碍物的方法,使机器人快速走出局部最小值区域。仿真结果验证了改进算法的有效性。

Improved artificial potential field algorithm for mobile robot obstacle avoidance path planning

This paper aims to solve difficult problems in mobile robot obstacle avoidance path planning based on improved artificial potential field (IAPF) algorithm. An obstacle boundary repulsion algorithm is designed to improve the performance of traditional artificial potential field algorithm for large obstacles. For the problem that robot, obstacle and target are located in the same line, a virtual sub-target gravity algorithm is proposed to ensure that the target is the global minimum of the robot potential field, and therefore the robot can arrive at the goal point. An obstacle isolation method is used for T-type obstacle situation which can solve the local minimum problem of potential field and help the robot go through quickly. Experiments are carried out by simulation to verify the effectiveness of the improved artificial potential field algorithm.