改进人工势场法的移动机器人路径规划研究  

Improved artificial potential field method for mobile robots path planning study

作　　者：倪建云 杜合磊[1,2] 谷海青 李浩 吴杰[2] 薛晨阳[2] NI Jianyun;DU Helei;GU Haiqing;LI Hao;WU Jie;XUE Chenyang(Tianjin Key Laboratory for Control Theory&Applications in Complicated Systems,Tianjin 300384,China;School of Electrical Engineering and Automation,Tianjin University of Technology,Tianjin 300384,China)

机构地区：[1]天津市复杂系统控制理论与应用重点实验室,天津300384 [2]天津理工大学电气工程与自动化学院,天津300384

出　　处：《重庆理工大学学报（自然科学）》2023年第11期247-256,共10页Journal of Chongqing University of Technology：Natural Science

基　　金：天津市自然科学基金项目(18JCYBJC87700)。

摘　　要：针对传统人工势场法存在目标不可达和局部极小值问题,提出一种改进的人工势场法。首先,改进斥力场函数解决目标不可达问题;其次,提出一种椭圆形目标策略,通过设置虚拟目标点引导机器人逃离局部极小值,在此基础上提出一种椭圆形跟踪策略,通过跟踪部分既定椭圆形到达虚拟目标点来逃离局部极小值;最后,为了满足机器人速度与加速度连续性的要求,采用3次均匀B样条曲线对规划出的路径进行拟合处理。实验结果表明,改进人工势场能够有效解决传统人工势场存在的问题,椭圆形跟踪策略在路径长度上比椭圆形目标策略更短,且经样条曲线处理后的路径比原路径平滑。In this paper,an improved artificial potential field method is proposed to address target unreachability and local minima in traditional artificial potential field method.First,the distance factor between the robot and the target point is introduced into the repulsive field function to solve the problem of unreachable target.Second,an elliptical target strategy is proposed to guide the robot to escape from local minima by setting virtual target points,on the basis of which an elliptical tracking strategy is proposed to escape from local minima by tracking a partially established ellipse to reach a virtual target point.Finally,to meet the continuity requirement of the robot velocity and acceleration,the planned path is fitted with a cubic uniform B spline curve.The experimental results show the improved artificial potential field method effectively remedies the problems of traditional artificial potential field method.The elliptical tracking strategy requires a shorter path length than the elliptical target strategy and after the sample curve processing,the path is smoother compared with the original one.

关 键 词：人工势场 目标不可达 局部极小值 椭圆形目标策略 椭圆形跟踪策略 B样条曲线 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP18[自动化与计算机技术—控制科学与工程]