Aiming at the problems of low planning efficiency

poor path quality and the existence of a large number of meaningless nodes when the improved swarm intelligence algorithm is planning path in the global environment

the egret swarm optimization algorithm(ESOA)is applied to the path planning of mobile robots and an improved ESOA combining the Tent chaotic mapping and the Lévy flight is proposed.The algorithm uses Tent mapping to initialize the egret population in the search stage to obtain better initial solutions;the regional limit method and Lévy flight are used to update the positions of individual egrets to reduce the path search cost and enhance the local search capability of the algorithm.In the optimization stage

the shortest path method and de-redundancy operation are used to remove the spike inflection points and meaningless nodes in the original path.Finally

the path is optimized by Bézier curves to obtain a smooth and continuous global path of the robot.Simulation results show that the algorithm outperforms the comparison algorithm in terms of path quality

number of robot turns

and number of path nodes.