一种基于改进人工势场法的局部路径规划算法  

A local path planning algorithm based on improved artificial potential field method

作　　者：许万[1] 程兆 朱力 张宇豪 Xu Wan;Cheng Zhao;Zhu Li;Zhang Yuhao(School of Mechanical Engineering,Hubei University of Technology,Wuhan 430068,China)

机构地区：[1]湖北工业大学机械工程学院,武汉430068

出　　处：《电子测量技术》2022年第19期83-88,共6页Electronic Measurement Technology

基　　金：船舶振动噪声重点实验室基金(6142204200709)项目资助。

摘　　要：针对在存在复杂障碍物的环境中,利用人工势场法进行移动机器人路径规划时出现的局部最小值和目标不可达问题。本文提出了一种基于凹形障碍物补齐的改进人工势场法进行局部路径规划。首先,通过对凹形障碍物补齐,防止机器人进入局部最小值区域。然后,通过新增距离影响因子,改进了斥力场函数,使目标点成为全局势场中的最小点,防止机器人陷入目标不可达区域。最后仿真结果表明,本文所提出的改进人工势场法可以解决存在复杂障碍物的环境中的局部最小值问题和目标不可达问题,并且相对于其他算法,可以有效减少路径补偿,提高规划效率。Aiming at the problem of local minimum and unreachable target when using artificial potential field method for mobile robot path planning in the presence of complex obstacles. In this paper, an improved artificial potential field method based on concave obstacle patching is proposed for local path planning. Firstly, the concave obstacles are filled to prevent the robot from entering the local minimum area. Then, by adding the distance influence factor, the repulsion field function is improved to make the target point the smallest point in the global situation field, and prevent the robot from falling into the target unreachable area. Finally, the simulation results show that the improved artificial potential field method proposed in this paper can solve the local minimum problem and the target unreachable problem in the environment with complex obstacles. Compared with other algorithms, it can effectively reduce the path compensation and improve the planning efficiency.

关 键 词：移动机器人 复杂障碍物 路径规划 人工势场法 障碍物补齐 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]