摘要：

针对人工势场(APF)法在机器人局部路径规划中存在的局部极小值陷阱和路径冗余等问题, 提出一种基于模糊控制(FC)和虚拟目标点改进人工势场的FC-V-APF算法。首先设计虚拟目标点避障策略, 并加入障碍物跨越机制和目标点更新阈值, 构建V-APF算法引导机器人摆脱陷阱区域; 其次提出基于累计转角和的控制策略, 帮助机器人走出多U型复杂陷阱; 然后针对路径冗余问题, 将V-APF算法与模糊控制算法相结合, 提出FC-V-APF算法, 通过激光雷达传感器的实时数据和权重函数对当前环境进行评估, 选取模糊控制器输出辅助力, 提前规避障碍物。最后在机器人操作系统(ROS)平台上搭建仿真环境对FC-V-APF算法进行路径规划性能的对比实验, 并对路径长度、运行时间和速度曲线等进行比较。实验结果表明, 所设计的FC-V-APF算法能够快速摆脱陷阱, 减少冗余路径, 提高路径平滑度并减少规划时间。

关键词: 机器人, 局部路径规划, 人工势场法, 虚拟目标点, 模糊控制

Abstract:

This study proposes an improved Artificial Potential Field (APF) algorithm (called FC-V-APF) based on Fuzzy Control (FC) and a virtual target point method to solve the local minimum trap and path redundancy issues of the APF method in robot local path planning. First, a virtual target point obstacle avoidance strategy is designed, and the V-APF algorithm is constructed to help the robot overcome local minimum traps by adding an obstacle crossing mechanism and a target point update threshold. Second, a control strategy based on the cumulative angle sum is proposed to assist the robot in exiting a multi-U complex obstacle area. Subsequently, the V-APF and FC algorithms are combined to construct the FC-V-APF algorithm. The corresponding environment is evaluated using real-time data from the radar sensor and designed weight function, and a fuzzy controller is selected to output the auxiliary force to avoid obstacles in advance. Finally, a simulation environment is built on the Robot Operating System (ROS) platform to compare the path planning performance of the FC-V-APF algorithm with that of other algorithms. Considering path length, running time, and speed curves, the designed FC-V-APF algorithm can quickly eliminate traps, reduce redundant paths, improve path smoothness, and reduce planning time.

Key words: robot, local path planning, Artificial Potential Field (APF) method, virtual target point, Fuzzy Control (FC)