Multi Robot Formation Control Based On Improved Particle Swarm Optimization Algorithm

With the continuous development of science and technology,in order to better complete some work and reduce the safety risks of staff,people have developed robots to help people complete some specific and dangerous work.In the process of robot application,path planning and formation control are two major research focuses in this field,and they complement each other.First,a new adaptive particle swarm optimization algorithm(IPSO)is proposed to overcome the shortcomings of the particle swarm optimization algorithm,such as the loss of population diversity,easy to fall into local optimum and poor convergence.This method combines the activation function in the neural network algorithm,and proposes the concept of population dispersion in the evolution process of particle swarm optimization algorithm in view of the shortcomings of particle swarm optimization algorithm.The information exchange between particles is effectively enhanced through particle rearrangement rules.Finally,the velocity updating formula of PSO is modified by introducing the elite mean deviation,and the effectiveness of the algorithm is proved through experimental simulation comparison.Secondly,the multi-robot architecture and the multi-robot formation control method are analyzed and introduced,and the problem of multi-robot tracking the navigator path in the ideal formation is studied.Combined with the artificial torque controller,the optimized particle swarm optimization algorithm is used to plan the robot path and the formation tracking control.The feasibility and validity of the robot motion model are verified by analyzing the motion models of the leader robot and the follower robot.Then,the obstacle avoidance strategy of the robot is studied.This paper takes the multi-robot system as the research object and carries out the algorithm simulation of the robot in the two-dimensional environment.By setting the initial conditions and rules of the robot,the optimized particle swarm optimization algorithm is used to plan the path of the robot,and the artificial torque controller is combined with the robot to carry out the steering output when acquiring the position node and the target node.This will drive each robot to move and finally complete the target task.Finally,the improved particle swarm optimization algorithm is simulated on the MATLAB simulation platform.After the simulation comparison before and after the improvement,the formation and control simulation of multi robot formation is completed.The feasibility and effectiveness of the new method are verified through the simulation platform.