复杂环境下群机器人自组织协同多目标围捕  

Self-organizing cooperative multi-target hunting by swarm robots in complex environments

作　　者：张红强[1] 吴亮红[1] 周游 章兢[3] 周少武[1] 刘朝华[1] ZHANG Hong-qiang;WU Liang-hong;ZHOU You;ZHANG Jing;ZHOU Shao-wu;LIU Zhao-hua(College of Information and Electrical Engineering,Hunan University of Science and Technology,Xiangtan Hunan 411201,China;College of Mechanical Engineering,Hunan University of Science and Technology,Xiangtan Hunan 411201,China;College of Electrical and Information Engineering,Hu’nan University,Changsha Hunan 410082,China)

机构地区：[1]湖南科技大学信息与电气工程学院,湖南湘潭411201 [2]湖南科技大学机电工程学院,湖南湘潭411201 [3]湖南大学电气与信息工程学院,湖南长沙410082

出　　处：《控制理论与应用》2020年第5期1054-1062,共9页Control Theory & Applications

基　　金：国家自然科学基金项目(61603132,61672226,61972443);湖南省自然科学基金项目(2018JJ2137,2018JJ3188,2018JJ2134);湖南省科技创新计划项目(2017XK2302);湖南省“湖湘青年英才”支持计划项目(2018RS3095);湖南科技大学博士科研启动基金项目(E56126);湖南省教育厅优秀青年项目(19B200);国防基础科研计划项目(JCKY2019403D006)资助.

摘　　要：针对动态多目标围捕,提出了一种复杂环境下协同自组织多目标围捕方法.首先设计了多目标在复杂环境下的运动模型,然后通过对生物群体围捕行为的研究,构建了多目标简化虚拟受力模型.基于此受力模型和提出的动态多目标自组织任务分配算法,提出了群机器人协同自组织动态多目标围捕算法,这两个算法只需多目标和个体两最近邻位置信息以及个体面向多目标中心方向的两最近邻任务信息,计算简单高效,易于实现.接着获得了系统稳定时参数的设置范围.由仿真可知,所提的方法具有较好的灵活性、可扩展性和鲁棒性.最后给出了所提方法相较于其它方法的优势.A self-organizing cooperative multi-target hunting method in complex environments is proposed for dynamic multi-target hunting. Firstly, the motion models of multi-target in complex environments are designed. Then, the multitarget simplified virtual-force model is constructed by researching the surrounding behavior of biological communities.Based on this force model and a proposed dynamic multi-target self-organizing task assignment algorithm, a cooperative self-organizing dynamic multi-target hunting algorithm by swarm robots is proposed. These two algorithms only need two kinds of information. One is the position information of multi-target and each robot’s two nearest neighbors, the other is the task information of each robot’s two nearest neighbors to the direction facing the multi-target center. Therefore, the new method is simple, efficient, and easy to implement. Then the parameter ranges for the stability of the system are given.Simulations results show that the proposed method has good flexibility, scalability, and robustness. Finally, the advantages of the proposed method over other methods are given.

关 键 词：移动机器人 群机器人 未知环境 动态障碍物 避障 多目标简化虚拟受力模型 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]