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<p>This study presents a comprehensive bibliometric analysis of published research on multi-agent formation control, aiming to provide an in-depth understanding of the current state and future prospects in this field. A total of 1,851 literatures retrieved from the Web of Science database were analyzed using bibliometric techniques and VOSviewer software. The analysis encompassed publication volume, geographical distribution, journal distributions, institutional affiliations, authorship networks, and keyword trends, thereby offering an objective overview of the research landscape and serving as a valuable reference for scholars. The findings reveal a steady annual increase in publication volume from 2000 to 2024, with China, the United States, and South Korea emerging as the top three contributors. Notably, China has led in publication volume since 2010, contributing 226 publications in 2024, which accounts for 75.8% of the total global publications. Among the most productive institutions, Beihang University stands out, contributing a substantial portion of the total publications. Additionally, International Journal of Robust and Nonlinear Control has been one of the leading journals in the field, consistently publishing high-impact research and contributing significantly to the academic discourse. High-frequency keyword analysis indicates that research hotspots in this domain include consistency control, formation tracking, obstacle avoidance, and system stability. Furthermore, this study discusses the structural frameworks, methodologies, and applications of multi-agent formation control, identifying critical future research directions such as limited observational data, stronger nonlinear dynamics, robust stability, unstructured environments, and heterogeneous agents. By synthesizing these insights, this study offers a valuable reference for advancing research in multi-agent formation control and underscores its potential for ongoing innovation. Ultimately, the findings clearly delineate current research gaps and propose directions for future studies, contributing to the development of more robust, efficient, and scalable multi-agent systems.</p>

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A bibliometric analysis on formation control for multi-agent system

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月28日

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  • Yong Xu,
  • Manping Qin,
  • Kui Fu,
  • Malathy Batumalay,
  • Choon Kit Chan,
  • Walton Wider,
  • Leilei Jiang,
  • Jiansheng Peng

摘要

This study presents a comprehensive bibliometric analysis of published research on multi-agent formation control, aiming to provide an in-depth understanding of the current state and future prospects in this field. A total of 1,851 literatures retrieved from the Web of Science database were analyzed using bibliometric techniques and VOSviewer software. The analysis encompassed publication volume, geographical distribution, journal distributions, institutional affiliations, authorship networks, and keyword trends, thereby offering an objective overview of the research landscape and serving as a valuable reference for scholars. The findings reveal a steady annual increase in publication volume from 2000 to 2024, with China, the United States, and South Korea emerging as the top three contributors. Notably, China has led in publication volume since 2010, contributing 226 publications in 2024, which accounts for 75.8% of the total global publications. Among the most productive institutions, Beihang University stands out, contributing a substantial portion of the total publications. Additionally, International Journal of Robust and Nonlinear Control has been one of the leading journals in the field, consistently publishing high-impact research and contributing significantly to the academic discourse. High-frequency keyword analysis indicates that research hotspots in this domain include consistency control, formation tracking, obstacle avoidance, and system stability. Furthermore, this study discusses the structural frameworks, methodologies, and applications of multi-agent formation control, identifying critical future research directions such as limited observational data, stronger nonlinear dynamics, robust stability, unstructured environments, and heterogeneous agents. By synthesizing these insights, this study offers a valuable reference for advancing research in multi-agent formation control and underscores its potential for ongoing innovation. Ultimately, the findings clearly delineate current research gaps and propose directions for future studies, contributing to the development of more robust, efficient, and scalable multi-agent systems.