基于改进人工鱼群算法的蠕虫机器人路径规划OA北大核心CSTPCD

Aiming at the problems of long paths,low accuracy and prone to local optima of the artificial fish swarm algorithm in robot path planning,an improved artificial fish swarm algorithm was proposed,which aimed to improve the efficiency and accuracy of the algorithm.An improved artificial fish swarm algorithm aimed at improving algo-rithm efficiency and accuracy was proposed in this study.Firstly,an optimization cycle was added to the algorithm's foraging behavior to reduce the randomness of the algorithm's selection of location points in path plan-ning,enabling the robot to move towards the target point faster.Then,the tabu search algorithm was integrated,and the tabu table was introduced to record the path where the algorithm might fall into the local optimum,so that the algorithm can avoid the local optimum region when selecting new location points,and could avoid the algorithm's local excessive cycle.At the same time,it could optimize the planned path,delete the paths between duplicate grid points,and ensure that there would be no duplicate grid points in the path.When the improved arti-ficial fish swarm algorithm was applied to a new type of 3D raster map,simulation experiments showed that com-pared to other comparative algorithms,the average path length obtained by improving the artificial fish swarm algo-rithm in maps 1,2 and 3 was reduced by 10%,15%and 30%,respectively,and the success rate of path planning in complex maps was increased by 75%.