引入模糊斥力的改进人工势场法及机器人局部路径规划

Local Path Planning Based on Improved Artificial Potential Field Using Fuzzy Repulsion Force for Robot

摘要: 针对传统人工势场法中存在的局部最小问题，提出一种引入模糊斥力的改进人工势场法。该算法首先在改进传统人工势场法的引力场和斥力场函数的基础上，通过确定引力场与斥力场增益的合理取值范围，解决目标位置靠近障碍物造成的目标位置不可达问题(GNRON)。接着利用模糊控制算法计算模糊斥力，并将其引入到改进人工势场法的机器人虚拟合力计算中，使得机器人在目标位置与起始位置间存在不同障碍物时仍能快速完成局部路径规划任务，进一步解决局部最小问题。仿真与室内模拟实验表明，运用该算法能够有效的解决局部最小问题。

Abstract: An improved artificial potential field method is proposed to solve the local minimum which exists in the traditional artificial potential field. First, on the basis of improving the attractive field and repulsive field functions of traditional artificial potential field, the problem on goals non-reacha- ble with obstacles nearby (GNRON) is solved by determining the reasonable range of gain of gra-vitational field and repulsive field. Then, the fuzzy control algorithm is used to calculate the fuzzy repulsion force and the situation when different obstacles are located between the robot and the goal is solved by calculating the virtual force using the fuzzy repulsion force which navigates the robot moving around the obstacle. At last, the proposed approach is verified by MATLAB simulation and indoor experiment, the results of which illustrate that the improved artificial potential field method is effective to solve the local minimal problem.