A Multi-agent Efficient Control System for a Production Mobile Robot

Abstract

This paper presents the results of the experiments of a multi-agent control architecture for the efficient control of a multi-wheeled mobile platform. Multi-agent system incorporates multiple Q-learning agents, which permits them to effectively control every wheel relative to other wheels. The learning process was divided into two steps: module positioning - where the agents learn to minimize the error of orientation and cooperative movement - where the agents learn to adjust the desired velocity in order to conform to the desired position in formation. From this decomposition every module agent will have two control policies for forward and angular velocity, respectively. The experiments were carried out with a real robot. Our results indicate the successful application of the proposed control architecture for the real production robot. © Springer International Publishing Switzerland 2014.