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集群多机器人系统建模研究的发展与展望
引用本文:王常虹,刘博,李清华.集群多机器人系统建模研究的发展与展望[J].导航定位于授时,2021,8(1):1-13.
作者姓名:王常虹  刘博  李清华
作者单位:哈尔滨工业大学空间控制与惯性技术研究中心,哈尔滨150001
基金项目:国家自然科学基金青年科学基金(61703123)
摘    要:凭借高效、鲁棒、应用广泛的特性,集群多机器人系统已经成为当今研究的热点课题之一,具有重要的实用价值。首先简述了自顶而下和自底而上两种多机器人系统研究思路的当前研究概况。然后从拟生物集群系统模型引入,进而引出一致性系统模型,针对低阶、高阶、异质、时延等一致性模型进行分析总结,单独阐述了多智能体强化学习系统模型的研究情况,并分别讨论了三种集群多机器人系统自组织建模方法的研究现状与各自存在的问题,总结与分析了集群多机器人系统运动的发生机理。最后,分析了现有集群多机器人系统模型尚待解决的关键问题和面临的挑战,并对其未来发展进行了展望。

关 键 词:多机器人系统  一致性控制模型  拟生物模型  多智能体强化学习模型

Multi-agent System Cooperative Navigation and Control Technology Development and Prospect of Research on Modeling of Swarm Multi-Robot System
WANG Chang-hong,LIU Bo,LI Qing-hua.Multi-agent System Cooperative Navigation and Control Technology Development and Prospect of Research on Modeling of Swarm Multi-Robot System[J].Navigation Positioning & Timing,2021,8(1):1-13.
Authors:WANG Chang-hong  LIU Bo  LI Qing-hua
Institution:Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, China
Abstract:Owning on the characteristics of high efficiency, robustness and wide application, the multi-robot system has become one of the research focuses, which has profound practical value. First, this paper describes the current research status of the top-down and bottom-up multi-robot system research briefly. Then, aiming to study the movement mechanism of multi-robot system, the modeling of self-organized multi-robot system is comprehensively introduced in aspects of consistency control model, quasi-biological model, and multi-agent reinforcement learning model, which are discussed in terms of research status and their problems. Finally, the key technologies and challenges of self-organized multi-robot system are summarized, and the trending issues are also delineated.
Keywords:Multi-robot system  Consensus model  Quasi-biological model  Multi-agent reinforcement learning model
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