一个复杂有界环境下的改进极限环避障算法

An improved limit cycle obstacle-avoiding algorithm in complex and confined environment

本文研究了障碍不规则与带边界这两种非预知环境条件下的群体运动实时规划问题,提出了一种改进极限环群体避障算法.该算法在传统极限环的基础上引入局部与包络的概念来解决障碍不规则的问题,另一方面通过改进传统人工势场的斥力函数来刻画边界的排斥作用,以避免与边界碰撞.针对不规则障碍与带边界这两种典型场景,本文在障碍与边界非预知的条件下进行了仿真实验.仿真结果表明,与传统人工势场法相比,本算法不仅减少了碰撞数量,缩短了避障时间,还具有更好的适应性和有效性.

We consider the real-time planning problem of swarm movement in complex environment with irregular obstacles and borders and propose an improved limit cycle obstacle avoiding algorithm.In this algorithm,the concepts of locality and envelope are borrowed from the traditional limit cycle.Then,by improving the repulsive force function of the traditional artificial potential field,the boundary repulsion is characterized in order to avoid collision with the boder.Finally,two simulations are implemented.The simulation results show that,compared with the traditional artificial potential field method,our algorithm can reduce the number of collisions and shorten the obstacle avoidance time adaptabily and effectively.