Optimization For Multi-robot Pattern Formation In Obstacle Environment

Multi-robot pattern formation is a hot topic in the research of multi-robot,which has received more and more attention.In practical applications,multi-robots form the desired patterns according to the requirements of different environments and tasks to complete such as area coverage,target search,formation performance,etc.However,most of the existing research on the multi-robot pattern formation is based on the ideal environment without obstacles and cannot be effectively applied to the obstacle environment.At the same time,in order to improve the efficiency of pattern formation,the multi-robot should further optimize the time and path length for pattern formation in addition to satisfying the desired pattern formation in the obstacle environment.Aiming at the above problems,this thesis studies the problem of optimizing multi-robot pattern formation in an obstacle environment establishes the goal pattern generation model considering the static obstacle constraint,and plans the collision-free path for the robot in real-time to form the goal pattern.Then the goal pattern can be formed dynamically in the environment of dynamic obstacles and the efficiency of pattern formation can be further improved by using the method of multi-robot group cooperation.Simulation results show the effectiveness and superiority of the algorithm.The main research contents of this thesis are as follows:1)This thesis aims at the problem that the existing multi-robot pattern formation algorithm cannot be effectively applied to the obstacle environment.Firstly,in the static obstacle environment,the optimal goal pattern generation model is established with the objective of optimizing the robot path and considering the constraint of the obstacle position information.At the same time,it is proved that the solution of this model belongs to the mixed-integer convex quadratic programming problem and has the global optimal solution.Then,based on the optimal position coordinates of the goal pattern,an iterative collision avoidance controller is designed to control the robot to reach the goal without collision in real-time to form the goal pattern.Finally,an experiment was designed on the Matlab simulation platform to verify the feasibility and convergence of the algorithm.2)The real environment usually contains dynamic obstacles.With the movement of dynamic obstacles,the environmental information changes all the time.Therefore,it is of more practical significance to solve the problem of optimizing the multi-robot pattern formation in the dynamic environment.Therefore,this thesis further studies the problem of optimizing multi-robot pattern formation in a dynamic obstacle environment and analyzes the conflict between dynamic obstacles and target patterns in the iterative motion process and dynamically solves the position of the optimal goal pattern.At the same time,the real-time control robot reaches the goal point without collision to form the goal pattern.Finally,the simulation experiment of letter patterns in the environment of dynamic obstacles is designed to verify the effectiveness and convergence of the algorithm.3)In order to further improve the efficiency of multi-robot pattern formation,an algorithm based on grouping is considered to optimize the multi-robot pattern formation.Firstly,the multi-robots are grouped by an improved grouping strategy.Then each group of robots completed its optimal pattern formation in parallel without collision through intra-group and inter-group coordination.The effectiveness and superiority of the algorithm are verified by analyzing the simulation results of multi-letter patterns.4)In order to reflect the application of multi-robot pattern formation in engineering background,this thesis designs an experiment of multi-robot letter pattern formation based on the collective Kilobot robot platform in the laboratory.Several experiments are conducted and the experimental results are analyzed to verify the repeatability and convergence of the experiment.