基于改进型人工势场的路径规划方法

Path Planning Method Based on Improved Artificial Potential Field

人工势场法作为机器人路径规划的一种经典算法,具有数学描述简单、运算快速等优点,但在使用人工势场法时,容易遇到局部极小值和目标点不可达问题。本文针对人工势场法局部极小值与目标点不可达问题,提出一种基于动态窗口法(DWA)的改进方法。当机器人遇到局部极小值或者目标点不可达问题后,选取机器人周围的路径点并对这些路径点进行评估,选取评估结果最好的路径点作为下一个路径点,重复以上步骤直至机器人逃离局部极小值或者到达目标点。在和传统人工势场法比较后的仿真结果表明,当机器人遇到局部极小值或者目标点不可达问题后,使用改进型人工势场法,可以有效地使机器人成功逃离局部极小值点并到达目标点。

Artificial potential field method is a classic algorithm for robot path planning.It has several advantages such as simple mathematical description and fast computing.However,it suffers from local minimum problem and target unreachable problem.In this paper,an improved artificial potential field method based on Dynamic Window Approach(DWA)is proposed to solve the local minimum problem and the target unreachable problem.When the robot encounters the local minimum problem or the target unreachable problem,it selects the way points around the robot and evaluate their performance.Choose the way point with the best evaluation result as the next way point and repeat the above steps until the robot escapes from the local minimum or reaches the target point.After compared with traditional artificial potential field method,the simulation results show that when the robot encounters the local minimum problem or the target unreachable problem,the improved artificial potential field method can help the robot successfully escape from the local minimum or reach the target point effectively.