Formation Coordination Control Of Robot Based On Multi-agent

With the rapid development of society and the rapid progress of science and technology of robots, people are increasingly concerned about the multi-robot systems, where the multi-robot coordination and control is an important issue in the field of robotics research, and in addition, combining the agent theory with multi-robot is a hotspot of current research. In this paper, coordination and control of the formation of multi-robot systems is researched based on multi-agent systems theory.Firstly, this paper introduces the research background and current status, pointing out the important theoretical and practical significance of the subject, then simply elaborates the basic theory of multi-agent formation control.Secondly, with help of theory of multi-agent systems, an agent architecture is designed.Followed, the forming problem of formation of multi-agent-based robot systems is studied:a relatively simple method of formation generation is designed according to the distribution of agent groups; an improved target optimal allocation method is proposed; a simulated annealing optimization allocation scheme is designed by applying simulated annealing method to multi-agent formation forming; the optimized decisions are compared to finalize the formation distribution; a motion controller is designed by means of the Control Lyapunov Function (CLF), and the simulation is conducted.Then, the formation and obstacle avoidance problem of multi-agent systems is analyzed and described:consistency formation diagram method is applied to the formation control, moreover a consistency arbitrary formation control law is designed; a hybrid avoidance strategy is proposed on the basis of artificial potential field method. And simulations in none or unknown obstacle maps are conducted and analyzed.Later, the transformation-related issues of multi-agent-based robot systems are discussed, then transformation conditions based on the angle information comparison is proposed, and the path tracking combined transformation strategy is studied.Finally, a summary of this paper is conducted, and gives further research prospect of this paper.