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

Abstract:

We consider the real-time planning problem of swarm movement in complex environments with irregular obstacles and borders and proposes an improved limit cycle group obstacle avoidance 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 adaptability and effectively.