一种复杂环境下移动机器人避障新方法

基于传统人工势场法的机器人避障算法虽然计算量小、实时性好,但在陷阱区域或在障碍物前可能产生震荡,导致机器人不能到达目标点,为解决上述缺陷,提出一种带记忆功能的沿边法。通过记录和分析障碍物边缘人工势场法的局部最小点来判断目标点是否被障碍物包围,从而避免机器人来回震荡和围着目标点旋转的发生。该方法步骤分为沿边行为激活和退出条件、局部最小点记录条件以及目标点被障碍物包围的判断准则。通过实验,结果表明该方法解决了复杂环境下机器人的避障问题。该方法用于复杂环境下的机器人避障是可行的、有效的。

A New Method for Mobile Robot Obstacle Avoidance UnderComplicated Environment

Though based on the traditional artificial potential field robot obstacle avoidance algorithm has small amount of calculation, goodness of real time, which may produce shock in the trap area or in front of the obstacle, and can"t reach target near obstacles, to solve the above drawbacks, a kind of edge followed method with memory function is proposed. Through recording and analyzing the local minimum points of obstacle edge artificial potential field method to determine whether the obstacle is surrounded by the target point, thus avoid that the robot move back and forward all the time or rotate around the target point. The step of this method is divided into the judgment criteria of the edge behavior activation and exit condition, the record of local minimum points and the estimation of target been surrounded by obstacles. Through the experiment, the results show that the method can solve the robot obstacle avoidance in complex environment. The method used to robot obstacle avoidance in complex environment is feasible and effective.