摘要
为了提高机器人在栅格环境下的路径规划质量,提出了基于超强启发式异类蚁群算法的路径规划方法。建立了机器人工作环境的栅格模型;在蚁群算法基础上,提出了由开创型蚂蚁、守旧型蚂蚁、传统型蚂蚁组成的异类蚁群算法,并通过仿真看出,开创型蚂蚁主导的异类蚁群算法具有最优性能;在信息素更新方面,按照“奖励先进、惩罚后进”的原则,提出了超强启发式信息素更新方法,引导传统型蚂蚁和守旧型蚂蚁快速向开创型蚂蚁搜索的较优路径靠近。经过仿真验证,异类蚁群算法在简单环境和复杂环境下规划的路径均优于传统蚁群算法,且异类蚁群算法寻优稳定性更好,寻优耗时更短。
In order to improve path quantity under grid environment,path planning method based on hyper-heuristic heterogeneous ant colony algorithm is proposed.Grid model of robot working environment is built.On the basis of ant colony algorithm,heterogeneous ant colony algorithm consist of creative ant,conservative ant and traditional ant is put forward.It can be seen that heterogeneous ant colony algorithm leading by creative ant possesses optimal property.In aspect of pheromone updating,according to the principle of“give awards to the advanced and punish the backward”,hyper-heuristic pheromone updating method is raised,which can make conservative ant and traditional ant close to better path searched by creative ant.Clarified by simulation,paths planned by heterogeneous ant colony algorithm under simple and complex environment are both shorter than the path planned by ant colony algorithm.Besides,optimizing steady of heterogeneous ant colony algorithm is better,and optimizing time-cost is shorter.
作者
刘钦
LIU Qin(Zhengzhou Vocational College of Finance and Taxation,Henan Zhengzhou 450048,China)
出处
《机械设计与制造》
北大核心
2021年第10期263-266,共4页
Machinery Design & Manufacture
基金
2019年度河南省重点研发与推广专项项目(192400410289)。
关键词
机器人路径规划
异类蚁群算法
超强启发式
开创型蚂蚁主导
Robot Path Planning
Heterogeneous Ant Colony Algorithm
Hyper-Heuristic
Leading by Creative Ant
