Obstacle Avoidance for Swarm Robot Based on Self-Organizing Migrating Algorithm
Quoc Bao Diep, Ivan Zelinka · Procedia Computer Science · 2019
This paper presents an obstacle avoidance algorithm for swarm robot in unknown environment based on self-organizing migrating algorithm in which the trajectory is divided into a set of points created by the SOMA that robot must pass through. During the move, obstacles will be detected by sensors on the robot, it only knows the target position without knowing the obstacles location until detecting them. The fitness function is based on the principle of attraction from the target and the repulsion of the obstacles, which helps robot find the trajectory for moving, and the ways leaving it to move safety away from the trapped area. Simulation results are also presented to show the feasibility of the algorithm.