摘要
在求解群机器人多目标搜索问题时,个体机器人之间的相互协作可以形成整体优化的效果。本文结合激发抑制原理,提出基于蜂群激发抑制的群机器人多目标协同搜索算法(AICA)。在个体层面进行细粒度协同,AICA通过激发抑制原理实现个体之间的紧密协作,快速形成子群体;在子群体层面进行粗粒度协同,使子群体之间能够进行进一步协同,充分发挥每个机器人的作用。仿真实验结果与分析讨论表明,AICA能够充分利用各个个体机器人和子群体在搜索过程中搜索到的信息,从而提升搜索效率,使群机器人能够以较高的效率完成搜索任务。
To solve the multi-objective search problem of swarm robots,the cooperation between individual robots can form the overall optimal effect.Based on the principle of activator inhibition,a swarm robot multi-target collaborative search algorithm(AICA)based on bee colony inhibition was proposed.Fine-grained collaboration at an individual level,AICA achieves close collaboration between individuals through the principle of activator inhibition,and quickly forms sub-groups;coarse-grained collaboration at the sub-group level enables further collaboration between the sub-groups and gives full play to each robot role.Simulation experiment results and discussion analysis show that AICA can make full use of the information searched by individual robots and subgroups in the search process,thus improving the search effi⁃ciency.The swarm robot can then complete the search task with high efficiency.
作者
肖人彬
曹勇
XIAO Renbin;CAO Yong(School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan,Hubei 430074,China)
出处
《河北工业大学学报》
CAS
2020年第5期1-14,共14页
Journal of Hebei University of Technology
基金
科技创新2030—“新一代人工智能”重大项目(2018AAA0101200)。
关键词
激发抑制
群机器人
多目标搜索
细粒度协同
粗粒度协同
activation-inhibition
swarm robot
multi-objective search
fine-grained collaboration
coarse-grained col⁃laboration
作者简介
肖人彬(1965—),男,教授,博士,博士生导师,rbxiao@hust.edu.cn。
