基于模糊改进人工势场法的机器人避障方法研究

Obstacle avoidance method research for robot based on fuzzy improved artificial potential field

在内部密封、狭窄、多障碍的船舱环境中,障碍物的分布具有随机性和不确定性,对于移动机器人的避障方法而言,传统人工势场法存在目标不可达、局部极小值等问题。设计了一种基于模糊逻辑的改进人工势场法,在避障算法的局部极小值附近,基于模糊逻辑给予移动机器人辅助控制力,帮助机器人逃离局部极小值点,避免机器人在避障过程中陷入局部极小值点的问题,并且优化路径。仿真实验表明:在多障碍复杂环境下,该算法能实现机器人实时、安全的避障。

In internal sealing, narrow, multi-obstacle cabin environment, distribution of obstacles are random and uncertain. In the case of obstacle avoidance for mobile robot, traditional artificial potential field method has problem of goal unreachable and inca] minimum value. An improved artificial potential field method based on fuzzy logic theory is designed to avoid these problems. In vicinity of local minimum of obstacle avoidance algorithm, auxiliary control force is given by fuzzy logic to help robot escaping local minimum value point. In process of obstacle avoidance, method can effectively avoid local minimum value point and optimize path. Simulation experiment show that in multi-obstacles complex environment the algorithm can achieve real-time and secure obstacle avoidance of robot.