Multi-robot Formation Control Technology Research Based On Improved Particle Swarm Optimization Algorithm

Multi-robot formation control technology which has a very wide range of applications is an important research direction in the study of multi-robot system, through which can complete many complex and dangerous mission. So the study of multi-robot formation control technology has important significance.The thesis uses the behavior and the virtual leader-follower method to research multi-robot formation control and improved particle swarm optimization algorithm to optimize the behavior weight parameters of the formation robots. Firstly, in terms of multi-robot formation control method, the thesis combines with the behavior method and leader-follower method to propose the behavior and the virtual leader-follower method, which sets the geometric center of the formation as a virtual leader robot and other entity robots as formation follower robots which put the virtual leader robot as a reference point to complete the formation task; secondly, the thesis establishes the environment model and the robot model and defines several basic behavior of the robot, uses vector synthesis method based on the Motor Schema structure for the vector synthesis of the basic behavior of the robot, puts the synthesis result as the robot’s behavior; after that in view of the basic particle swarm optimization algorithm with stationary inertia weight which makes the slower convergence speed and the lower convergence precision problem, the thesis proposes the improved particle swarm optimization algorithm with dynamic inertia weight, which nonlinearly decreases inertia weight in the process of iteration algorithm and improves the convergence speed and convergence precision of the algorithm; finally using improved particle swarm optimization algorithm to optimize behavior weight parameters of the formation robots, the thesis proposes the multi-robot formation control algorithm based on improved particle swarm optimization algorithm, which is simulated in MATLAB, and compares with the results before optimization to prove that the multi-robot formation control algorithm based on improved particle swarm optimization algorithm is effective.Experimental results show that, improved particle swarm optimization algorithm has the faster convergence speed and the higher convergence precision and can find a better global optimal value; using improved particle swarm optimization algorithm to optimize the behavior weight parameters of the formation robots can effectively improve the formation property and also proves that the multi-robot formation control based on improved particle swarm optimization algorithm has feasibility and validity.