Collision Avoidance in Multi-Robot Environment based on Local Communication.

Abstract

In this paper, we propose a new collision avoidance method among multiple autonomous mobile robots. Generally, it is difficult to apply conventional collision avoidance methods to robots in multi-robot environment because those methods are only applicable to a single robot environment. For this problem, we propose a new method using the LOCISS (LOcally Communicable Infrared Sensory System) by which a robot is able to communicate with other robots locally to exchange information necessary for their mutual collision avoidance. To realize the collision avoidance based on these information, we introduce a learning method by which a robot is able to acquire the behavior adaptively and autonomously. A learning curriculum is divided into multiple layers to reduce a number of situation for the learning. Finally, we implemented this system to execute acquired behaviors, so that robots can avoid other robots and obstacles at the same time. It is confirmed by conducting experiments that this method is effective in the multi-robot environment.