Research On Path Planning And Cooperative Target Assignment Algorithms Of Autonomous Mobile Robots

In robotics,path planning and cooperative target assignment are important research fields.And,they are also the key technology and cornerstone for autonomous mobility and efficient completion tasks of robots,with characteristics of complexity,constraint and nonlinearity.The research is of great significance both in theory and in practical applications.In solving the path planning problem of mobile robot,the existing optimization algorithm are often accompanied by such shortcomings as poor robustness,non-optimal,slow convergence speed and difficult parameter setting.The multi-robot system has the advantages of strong robustness and more reliability,etc.However,in the multi-robot system,the assignment of cooperative target has always been a problem that needs to be solved urgently.Therefore,in order to improve the performance of path planning and the efficiency and accuracy of multi-target assignment,this paper proposes the corresponding algorithm to solve the above problems,so as to enhance the efficiency and ability of mobile robot to perform tasks.The main research contents of this paper include:1.Optimize the A* algorithm planning path by cubic B-spline function smoothing.Using MATLAB to build the simulation environment,the A* algorithm was compared in three different simulation environments.After the comparison and analysis of experiment,in view of the A* algorithm in the process of simulation experiment of partial path area turning angle was too large,the path was not smooth,and there were path spikes.Adopt a scheme of smoothing the path based on cubic B-spline function,and verify the feasibility of the scheme.Improve proposals can eliminate path spikes and reduce path cost.2.Improved Teaching-Learning-Based Optimization(TLBO)algorithm was proposed and applied to robot path planning.After analyzing the principle and defects of TLBO algorithm,an improved scheme is proposed,which increases the weight factor of efficiency degree and adopts the elite strategy.The improved ITLBO algorithm was applied to the path planning of mobile robots.An environment model was established and simulation experiments were conducted to verify that the ITLBO algorithm could effectively provide feasible paths.The improved algorithm provided a higher convergence rate and a better feasible path.Finally,the impact of parameter selection on the ITLBO algorithm is analyzed.3.A Dual-strategy Differential Evolution(DSDE)algorithm with Affinity Propagation(AP)clustering was proposed to solve the problem of multi-machine cooperative target assignment in a three-dimensional environment.The dual-strategy mutation scheme is adopted,an adaptive probabilistic selection mechanism based on AP clustering is introduced.After analyzing the time complexity of the new algorithm,the validity of the scheme is verified by simulation experiments.The results show that the algorithm not only maintains the diversity of the population,but also obtains more global optimal solutions,and improves the accuracy and convergence speed of the target assignment.