复杂环境下解决势场法局部极小问题的路径规划方法

A Method for Solving Local Minimum Problem of Path Planning Based on Potential Field in Complex Environments

多年来势场法路径规划的局部极小问题就一直被广泛关注,针对人工势场法所固有的缺陷提出了一种改进的移动机器人路径规划方法.方法利用膨胀与腐蚀算法对机器人的工作空间进行预处理,来优化工作环境,并使用改进的势场法进行机器人导航,以改善其运动轨迹;另外通过设置子目标点使陷入局部极小的机器人快速"逃离"极小状态.仿真结果表明本文算法在复杂环境下解决机器人路径规划的局部极小问题是有效的.

The local minimum problem of path planning based on potential field has attracted attention for many years. For the innate limitations of potential field, an improved method for moblie robot path planning is proposed in this paper. In this method, expansion and erosion algorithms are used to pretreat and optimize the workspace of robot and improved potential field is used to navigate robot. Furthermore, sub-goal point is set for robot to get rid of local minimization rapidly. The simulation results indicate that this method is effective to solve local minimum problem for robot path planning in complex environments.