改进人工势场法的移动机器人局部路径规划

Local path planning for mobile robot based on improved artificial potential field method

针对传统人工势场法存在的局部极小点问题,提出了基于虚拟目标点和环境判断的改进方法,实现移动机器人的局部路径规划。当移动机器人陷入局部极小点陷阱时,设置虚拟目标点,引导机器人跳出局部极小点陷阱;同时加入环境判断条件,判断机器人是否处于近似封闭的障碍物环境中,是否有绕圈而无法到达目标点的危险;最后,对改进算法进行了仿真验证。结果表明,加入判断条件的虚拟目标点法在可能存在陷阱区域的运行环境(如一字型障碍物、U型障碍物、近似封闭的障碍物和混合障碍物)下,均能顺利到达目标点。

This paper proposed an improved artificial potential field method for the local path planning task of the mobile robot. The algorithm combines the virtual target point method and the method of environment judgement parameters to solve the problem of local minima that exists in the traditional artificial potential field method. When the robot falls into the local minimum trap, the virtual target point is set to guide the robot to jump out of it. Meanwhile, the environment conditions are added to judge whether the robot locates at a nearly closed obstacle environment, and is in a risk of failing to arrive at the target point because of circling. Finally, the proposed algorithm is verified by simulations. The results show that the improved algorithm based on the virtual target point method with judgment conditions can successfully reach the target point under the linear obstacle, U-shaped, nearly closed obstacle environment and mixed obstacle environment, respectively.