计算机科学与探索 ›› 2022, Vol. 16 ›› Issue (8): 1706-1726.DOI: 10.3778/j.issn.1673-9418.2201057

• 综述·探索 • 上一篇    下一篇

集群机器人空间协作行为模型构建方法综述

赵月, 沈博(), 武文亮, 周兴社   

  1. 西北工业大学 计算机学院,西安 710129
  • 收稿日期:2022-01-18 修回日期:2022-04-01 出版日期:2022-08-01 发布日期:2022-08-19
  • 通讯作者: +E-mail: shen@nwpu.edu.cn.
  • 作者简介:赵月(1986—),女,博士研究生,主要研究方向为群体智能评价。
    沈博(1985—),男,博士,副教授,主要研究方向为信息物理融合系统、物联网等。
    武文亮(1989—),男,博士研究生,主要研究方向为群体智能评价。
    周兴社(1955—),男,教授,博士生导师,主要研究方向为嵌入式计算与分布计算、信息物理融合系统等。
  • 基金资助:
    国家部委科技创新特区计划课题基金;国家自然科学基金(61902295)

Survey on Modeling Method of Spatial Cooperative Behavior of Swarm Robots

ZHAO Yue, SHEN Bo(), WU Wenliang, ZHOU Xingshe   

  1. School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an 710129, China
  • Received:2022-01-18 Revised:2022-04-01 Online:2022-08-01 Published:2022-08-19
  • About author:ZHAO Yue, born in 1986, Ph.D. candidate. Her research interest is the evaluation of swarm intelligence.
    SHEN Bo, born in 1985, Ph.D., associate professor. His research interests include cyber-physical systems, Internet of things, etc.
    WU Wenliang, born in 1989, Ph.D. candidate. His research interest is the evaluation of swarm intelligence.
    ZHOU Xingshe, born in 1955, professor,Ph.D. supervisor. His research interests include embedded computing and distributed computing, cyber-physical systems, etc.
  • Supported by:
    the National Science and Technology Innovation Special Zone Project;the National Natural Science Foundation of China(61902295)

摘要:

集群机器人是由一定数量的物理机器人组成,该系统中的个体通过交互与协作,可涌现出鲁棒、可扩展、灵活的群体智能行为。集群机器人行为建模是科学分析此类系统的基本方法之一,也是其能力评估的重要基础,研究与分析集群机器人行为模型有助于理解其行为机理。首先对集群机器人的主要特性进行总结,列举了几种典型的集群机器人空间协作行为;在此基础上,对集群机器人空间协作行为进行分类,重点总结和阐述了集群机器人空间协作行为的建模方法,包括图论、仿生模型、动力学模型以及学习模型,从方法概述、应用实例与适用场景等多维度对各类建模方法进行了分析与比较。最后提出了集群机器人空间协作行为建模有待进一步深化研究的问题,并对其未来可能的研究方向进行了展望,以更好地支撑集群机器人系统评估与优化设计。该研究旨在使相关研究人员全面系统地理解集群机器人空间协作行为建模方法。

关键词: 集群机器人, 群体行为, 建模方法, 仿生模型, 学习模型

Abstract:

Swarm robots are composed of a certain number of physical robots. Through interaction and cooperation, individuals in this kind of system can sprout robust, scalable and flexible swarm intelligence behavior. Behavior modeling of swarm robots is one of the basic methods for scientific analysis of such systems, and it is also an important basis for its capability evaluation. The research and analysis of behavior model of swarm robots is helpful to understand its behavior mechanism. Firstly, this paper summarizes the main characteristics of swarm robots, and lists and summarizes several typical spatial cooperation behaviors of swarm robots. On this basis, the spatial cooperation behavior of swarm robots is classified, and the modeling methods of spatial cooperation behavior of cluster robots are summarized and expounded, including graph theory, bionic model, dynamic model and learning model. Various modeling methods are analyzed and compared from the multi-dimensional aspects of method overview, application examples and applicable scenes. Finally, the problems of spatial cooperative behavior modeling of swarm robots to be further studied are put forward, and possible research directions in the future are prospected, so as to better support the evaluation and optimization design of swarm robots. The purpose of this paper is to enable relevant researchers to comprehensively and systematically understand the spatial cooperative behavior modeling method of swarm robots.

Key words: swarm robots, swarm behavior, modeling method, bionic model, learning model

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