Research On The Control Of Flocking Motion With Obstacle Avoidance Of Multi-robot

Recently, the research on Motion Planning of Multi-Robot has gradually become a hot topic in robotics research. Motion Planning of Multi-Robot includes this three control acts: path planning, formation control, and obstacle avoidance. In a large number of motion coordination algorithms, a special kind of coordinated approach--flocking control mode--has caused great concern in the theory of intelligent systems research at home and abroad. Flocking is a new method of decentralized control which imitates the cluster of the biological movement in the nature. It is conducive to realize the formation control and coordination control of the multi-agent systems. Flocking control of the multi-robot enables the robots has separation,alignment,and cohesion, so that a team of robots could maintain a desired formation in the movement, and to provide the system with redundancy and structural flexibility. This article has carried out a further research on motion control and obstacle avoidance control of the flocking of multi-robot: an idea of complex networks is introduced to model. A decentralized control method is used to control intelligent groups distributed. The topology model of dynamic network of intelligent groups has been combined with artificial potential field. For that, the robots could move to the target with a stable formation in the flocking movement; limit-cycle method for flocking motion with obstacle avoidance in global unknown environment is studied. The limitations of the shape of the obstacle have been overcome. And the limit-cycle method makes the swarm avoid obstacles smoothly; furthermore the paper carried out a series of simulation experiments for the formation control algorithm and obstacle avoidance control algorithm, and analyzed the simulation results. The simulation consists of two parts: MATLAB simulation and analysis; through a new open source robot simulation platform: Player/Stage to establish the simulation system. The simulation results show that multiple robots could move over the obstacles and reach the target with a smooth and stable formation. Therefore, the correctness and stability of the algorithm has been verified.