Open Access

REVIEW

Recent Advancement in Formation Control of Multi-Agent Systems: A Review

Aamir Farooq¹, Zhengrong Xiang^1,*, Wen-Jer Chang^2,*, Muhammad Shamrooz Aslam³

1 School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China
2 Department of Marine Engineering, National Taiwan Ocean University (NTOU), Keelung City, 202301, Taiwan
3 Artificial Intelligence Research Institute, China University of Mining and Technology, Xuzhou, 2211106, China

* Corresponding Authors: Zhengrong Xiang. Email: ; Wen-Jer Chang. Email:

Computers, Materials & Continua 2025, 83(3), 3623-3674. https://doi.org/10.32604/cmc.2025.063665

Received 20 January 2025; Accepted 24 April 2025; Issue published 19 May 2025

Abstract

Formation control in multi-agent systems has become a critical area of interest due to its wide-ranging applications in robotics, autonomous transportation, and surveillance. While various studies have explored distributed cooperative control, this review focuses on the theoretical foundations and recent developments in formation control strategies. The paper categorizes and analyzes key formation types, including formation maintenance, group or cluster formation, bipartite formations, event-triggered formations, finite-time convergence, and constrained formations. A significant portion of the review addresses formation control under constrained dynamics, presenting both model-based and model-free approaches that consider practical limitations such as actuator bounds, communication delays, and nonholonomic constraints. Additionally, the paper discusses emerging trends, including the integration of event-driven mechanisms and AI-enhanced coordination strategies. Comparative evaluations highlight the trade-offs among various methodologies regarding scalability, robustness, and real-world feasibility. Practical implementations are reviewed across diverse platforms, and the review identifies the current achievements and unresolved challenges in the field. The paper concludes by outlining promising research directions, such as adaptive control for dynamic environments, energy-efficient coordination, and using learning-based control under uncertainty. This review synthesizes the current state of the art and provides a road map for future investigation, making it a valuable reference for researchers and practitioners aiming to advance formation control in multi-agent systems.

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Keywords

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