基于改进鸡群优化算法的食品拣取机器人路径规划

Path planning of food sorting robot based on improved chicken swarm optimization algorithm

目的:优化多工位食品拣取机器人路径。方法:提出了一种基于改进鸡群优化算法(Improved Chicken Swarm Optimization, ICSO)的食品拣取机器人路径规划方案,充分考虑单个工位点机器人最优拣取位置和多工位点之间机器人移动最短距离,构建多工位食品拣取机器人路径规划双层模型。利用密度峰值聚类算法对种群进行聚类分析,重新定义个体编码方式和更新进化机制,并采用ICSO对路径规划双层模型进行求解,从而实现食品分拣和机器人移动最短路径求解。结果:相比于其他路径规划方法,基于改进鸡群优化算法的食品拣取机器人路径规划方案总路径缩短了7.3%~16.7%,运行时间减少了8.14%~39.33%。结论:所提方案提高了食品分拣机器人路径规划效率,具有较好的实际应用价值。

Objective: In order to improve the efficiency of path optimization of multi station food sorting robot, a path planning scheme of food sorting robot based on improved chicken swarm optimization algorithm is proposed. Methods: The two-level path planning model of multi station food sorting robot was constructed by fully consider the optimal picking position of the robot at a single station and the shortest moving distance of the robot between multiple stations. The improved chicken swarm optimization(ICSO) algorithm was designed. The density peak clustering algorithm was used to cluster the population of ICSO, and the individual coding mode and the evolution update mechanism were redefined. Finally the ICSO was used to solve the double-layer model of path planning, so as to solve the shortest path of food sorting and robot movement. Results: Compared with other path planning methods, the total path was shortened by 7.3%~16.7% and the running time was reduced by 8.14%~39.33%. Conclusion: The proposed scheme improves the path planning efficiency of food sorting robot and has good practical application value.