Improved Mushroom Reproduciton Optimization for Robot Path Planning

Abstract

In order to improve the performance of mushroom reproduction algorithm in path planning, an improved mushroom reproduction algorithm is proposed. Chaotic map is used to initialize to improve the ergodicity of the initial population. Introducing levy flight to avoid the algorithm falling into local optimum.To make the algorithm have adaptive local search ability, chaotic weight mechanism is proposed. Judgment factors are optimized to make the artificial wind judgment conditions change with iteration. The path planning is tested in navigation point model, and the path is smoothed by cubic spline interpolation. Simulation experiments are carried out in different obstacle maps, the results show that the improved mushroom reproduction algorithm has better effect than the mushroom reproduction algorithm and other swarm intelligence algorithm in path planning.