基于改进人工势场法的移动机器人路径规划

针对势场法的障碍物附近目标不可达的问题，改进了传统人工势场斥力函数，确保目标点是机器人的势场全局最小点，使得机器人顺利到达目标点。针对势场法的局部最小值问题，提出了一种连接局部最小值区域障碍物的方法，建立了机器人离散传感器模型，使机器人快速走出局部最小值区域。改进后的人工势场法适用于复杂室内环境下的机器人路径规划。仿真结果证明了该方法的有效性。

Path planning of mobile robot based on improved artificial potential field

This paper utilized an improved artificial potential field to solve the problem of Goals Nonreachable with Obstacle Nearby （GNON）. The improved artificial potential field adopted the improved potential function that ensured the goal is the global minimum so the robot can reach the goal freely. To address the local minimum problem in classical potential field method, a method composed of obstacles connection and discrete model of sensor of robot was proposed. The improved method was adaptable to path planning of robots in complex indoor environment. The effectiveness of the improved algorithm was verified by simulation.