Collision avoidance planning in multi-robot based on improved artificial potential field and rules

Abstract

For the real-time and distributed features of multi-robot system, the strategy of combining the improved artificial potential field method and the rules based on priority is used to study the collision avoidance planning problem in multi-robot systems. The traditional artificial potential field method has some drawbacks, improved artificial potential field based on simulated annealing algorithm satisfactorily resolved this issue, so robots can found a local collision-free path in the complex environment. Through the robot's movement vector trail, collisions between robots can be detected, thereby activate the collision avoidance rules. Coordination between the robots by the priority based rules improves the real-time property of multi-robot system well. The combination of these two methods can make robot to find a collision-free path from a starting point to the goal quickly in an environment with many obstacles. Finally, the VC-based simulation environment tests the feasibility of the method.