| In recent years,with the complexity of robot application scenarios and the diversification of tasks,multi-robot collaborative formation control has become a research hotspot.In practical applications,robots in the system form a desired formation to complete tasks such as formation round-up,formation performance,area search,etc.However,with the complexity of the tasks to be completed and the variability of the environment,new and higher requirements are put forward for the research of multi-robot formation control algorithms,such as,the algorithm needs to be able to improve the formation efficiency and optimize the formation path,at the same time the controller needs to have strong universal adaptability,robustness and adaptive ability.In view of the above problems,this thesis considering the complexity of the algorithm and the performance of the system,the multi-robot formation problem is studied,and the experiments are designed to verify the effectiveness and superiority of the algorithm.The main research contents of this thesis are as follows:(1)In this thesis,aiming at the problems of low formation efficiency and large system overshoot in the multi-robot formation control algorithm under complex conditions,a multi-robot system formation controller is designed that comprehensively considers formation efficiency and system overshoot.Firstly,the kinematics of the mobile robot is analyzed,and a virtual pilot robot is introduced in the leader-follower structure model to establish a follower-virtual leader tracking control structure model,and the position error relationship between the robots in the control model is analyzed.Then,according to the relationship between the system error and the speed of the robot in the control model,combined with the formation tracking control law in the previous literature,a new control law with wider application range is designed,and the stability of the control law is theoretically verified.Finally,a comparative experiment is carried out to compare the control law in this thesis with the control law in the previous literature.The simulation results show that the control law in this thesis can improve the formation efficiency and reduce the overshoot of the system.At the same time,the influence of the control law on the system performance is analyzed through experiments.(2)In order to further improve the efficiency of multi-robot formation and the adaptive ability and stability of the controller,aiming at the problem that the adjustment parameters in the control law affect the formation effect and cannot change adaptively,a fuzzy adaptive multi-robot formation control algorithm is considered in this thesis.Firstly,the system error and the error change rate are selected as the input of the fuzzy controller,and the parameter values are used as the output,and a dual-input singleoutput fuzzy controller is designed.Then,a experiment is designed to compare the multi-robot formation effect under the control of fuzzy control parameters and fixed parameters.At the same time,based on the comparison of the experimental results,the Monte Carlo algorithm is further used to traverse multiple parameter combinations within the parameter value interval.The optimal parameters of the system are selected and compared with the fuzzy control parameters.The experimental results show that the fuzzy control parameters can improve the formation efficiency,improve the stability and flexibility of the system,and optimize the formation path.Finally,in order to reflect the application of the algorithm in the engineering background,this thesis combines the multi-robot fuzzy adaptive formation algorithm with the round-up strategy,and the multi-robot formation round-up experiment is designed.The experimental results show that the algorithm in this paper can complete the multi-robot formation round-up task.(3)In order to reflect the application of the algorithm in this thesis in the real environment,the simulation experiment and physical experiment of multi-robot formation are designed on the Pioneer3 robot in the laboratory.The physical experiment is affected by its own and external factors,and the formation effect of the physical experiment will have a certain gap compared with the simulation experiment,but the results show that the algorithm in this thesis can complete the multi-robot formation task in the real environment. |
