Hierarchical Path Planning Method For Multiple Mobile Robots Based On Bezier Curve Fusion Improved Genetic Algorithm

The ever-changing science and technology have allowed multi-mobile robots to gradually enter people's lives.With the ever-increasing demand for production and life,a single mobile robot can no longer complete complex tasks on its own.Therefore,multi-mobile robot system emerges as the times require and becomes the research hotspot of current science and technology.The path planning problem of multiple mobile robots is the key point to realize its autonomous navigation,and it is the premise of whether multiple mobile robots can be used in real life.This problem takes multiple mobile robots as the research object,and the purpose is to plan a collision-free optimal feasible path for each mobile robot in the same operating space.This paper mainly studies the path planning problem of multiple mobile robots in static environment,and carries out an in-depth study on the optimization of planning algorithm and the coordination of collision avoidance among mobile robots.The specific work contents are as follows:(1)The Bezier curve fusion improved genetic algorithm is proposed to solve the path planning problem of a single mobile robot.This algorithm is improved for the defects of traditional genetic algorithm,such as easy to fall into local optimum and slow convergence speed.Specific optimization points include:using a heuristic median insertion method to generate an initial feasible path and speeding up the convergence of the algorithm;setting a multi-objective fitness function based on the three indicators of path length,path safety,and path energy consumption to improve the quality of the planned path;using the layering method,single point crossover method and eight neighborhood single point mutation method to design the selection,crossover and mutation operators respectively;introducing the concept of Bezier curve,the path sequence points generated by the above improved genetic algorithm are used as the control points of Bezier curve,and a smoother curve path that is more in line with real life is obtained.(2)A hierarchical path planning method is proposed,which divides the path planning problem of multiple mobile robots into two stages based on global and local planning ideas.In the first stage,a global initial feasible path is planned for each mobile robot based on the proposed Bezier curve fusion improved genetic algorithm;in the second stage,collision prediction between mobile robots is carried out,the collision area and conflict type are determined,and the corresponding conflict resolution mechanism is selected to achieve the purpose of coordinated collision avoidance.The two stages are combined to plan the global collision free optimal path of multiple mobile robots(3)Use MATLAB software to establish a grid model and carry out corresponding simulation experiments.The experimental results show that Bezier curve fusion improved genetic algorithm can realize the path planning of a single mobile robot in different specification environments.Compared with the traditional genetic algorithm and other algorithms proposed in other literature,the optimal path obtained from the planning has significant advantages in path length,path smoothness and algorithm running time.The multi-service robot path planning example in complex static environment verifies that the hierarchical path planning algorithm can successfully plan the global collision free optimal path of each service robot.And it can be well applied to the actual situation of path planning problem of multi-mobile robot.