Robot Path Planning Based On Improved Mushroom Repeoduction Algorithm

Path planning is the key technology of robot navigation.In this paper,we select the mushroom reproduction optimization(MRO)algorithm for path planning,but the mushroom reproduction algorithm is still easy to fall into local optimization and low convergence accuracy.Therefore,this paper optimizes the mushroom reproduction algorithm and tests it from multiple test functions to verify the performance of the improved algorithm;Mushroom reproduction algorithm is used to solve the problem of robot path planning.By investigating the idea and principle of traditional mushroom propagation algorithm and the application of various swarm intelligence algorithms in robot path planning and the problem of robot path planning,a robot path planning method based on chaotic mapping and Levy flight is proposed.The specific research contents are as follows(1)Based on the basic mushroom reproduction algorithm,a mushroom reproduction algorithm based on chaotic map and Levy flight is proposed to improve the algorithm's poor global search ability and easy to fall into local optimum.Compared with MRO,this algorithm makes four improvements.Firstly,the chaos initialization mechanism is introduced to increase the ergodicity of the initial population;Secondly,Levy flight mechanism is used to make Levy flight strategy for the group at the end of each iteration,and greedy selection mechanism is used to make the algorithm have the ability to jump out of the local optimum;Secondly,a nonlinear factor is used to improve the global capability of the algorithm;Finally,the chaotic weight mechanism is used to improve the local search ability of the algorithm.The advantages of the proposed method are verified by testing on 12 test functions.(2)In order to solve the problem of robot path planning,mushroom reproduction algorithm is prone to fall into local optimum,instability and slow convergence.A new path planning method based on improved mushroom reproduction algorithm is proposed.The idea of chaos mapping,Levy flight and nonlinear factor in(1)is used to improve the basic mushroom reproduction algorithm,The difference is that using Levy flight strategy after falling into local optimum is equivalent to giving disturbance information when falling into local optimum.At the same time,aiming at the path planning problem,the initial position of the group is reduced.Then the path planning problem is transformed into an improved mushroom reproduction algorithm to optimize the nonlinear interpolation control points to reduce the dimension of the problem.Simulation results show that the proposed method has faster convergence speed,better stability,higher accuracy,can avoid local optimization to a certain extent,and the obtained path is smooth and shorter.