Research On Path Planning Of Mobile Robot Based On AGA-WOA Hybrid Algorithm

As an important part of mobile robots,AGV guided car needs to be navigated through autonomous path planning.Most factories and warehouses in real life are large in area and complex in environment.It is particularly important to explore the path planning method from static simple environment to dynamic relatively complex real-time environment.The research of AGA-WOA hybrid algorithm in this paper is mainly to satisfy the autonomous path planning when AGV accesses and accesses vehicles.Its task is to find an optimal collision-free path for each AGV from pre-stored parking space to target parking space in a static to dynamic environment,and to complete all the path planning tasks in an orderly manner.In this paper,the AGA-WOA hybrid algorithm for path planning is proposed to satisfy the autonomous path planning of AGV when accessing vehicles.Its task is to find the best collision-free path from the reserved parking space to the target parking space for each AGV in the static to dynamic environment,so as to complete all the path planning tasks.In this paper,the fitness function of genetic algorithm is improved by introducing difference function,and a series of genetic operations including selection operator,crossover and mutation are adopted to form a new improved genetic algorithm,which improves the optimization efficiency of genetic algorithm.In order to make up for the problem of local optimization and low convergence of genetic algorithm,a hybrid optimization algorithm based on improved genetic algorithm and whale optimization method is proposed to improve the adaptability of mobile robot path planning to complex environment.Whale optimization algorithm is used to reduce the number of iterations required by genetic algorithm.The method of continuously updating whales is used to optimize the chromosomes of genetic algorithm and replace the poor chromosomes with good chromosomes.The idea of combining improved genetic algorithm with whale optimization algorithm can effectively reduce the problems of local optimal solution,long convergence time and unstable optimization result of traditional genetic algorithm,so that mobile robots can search target results faster,avoid repetitive operation process,and continuously optimize genetic operators.The simulation analysis is carried out by MATLAB,and the simulation and experiment are carried out by using AGA-WOA hybrid algorithm in dynamic and static environments respectively,and the experimental results are compared.It is verified that the method of constructing basic genetic algorithm based on whale optimization algorithm is effective in path planning under dynamic and static environment,and has achieved good results in convergence speed,optimization effect,optimization ability and dynamic convergence.In order to verify the validity of the simulation results in both dynamic and static environments,the randomness of the proposed algorithm is avoided.In this paper,the experimental platform is built to let the car use the proposed algorithm in the actual environment.The results show that the efficiency of AGA-WOA hybrid algorithm for path planning is significantly better than the traditional genetic algorithm,which verifies the effectiveness of the algorithm.