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This paper presents a novel control framework for multi-agent systems that ensures convergence while avoiding entangled dynamics, offering significant potential for scalable robotics and decentralized coordination tasks. By addressing long-standing challenges in time-varying formation control and safe navigation within dense environments, the work advances core methodologies essential for complex autonomous system design. The focus remains strictly on algorithmic synthesis and theoretical guarantees rather than consumer applications or general computing infrastructure.
Disentangled Control of Multi-Agent Systems
arXiv:2511.05900v4 Announce Type: replace-cross Abstract: This paper develops a general framework with convergence guarantees for multi-agent control synthesis, which applies to a wide range of problems, including those with time-varying objective functions. The proposed framework achieves decentralization without inducing entangled dynamics among agents, and it naturally supports multi-objective robotics and real-time implementation. To demonstrate its generality and effectiveness, the framework is applied to three representative problems, namely time-varying leader-follower formation control, decentralized coverage control for time-varying density functions, which is a long-standing open problem, and safe formation navigation in a dense environment.
Abstract:This paper develops a general framework with convergence guarantees for multi-agent control synthesis, which applies to a wide range of problems, including those with time-varying objective functions. The proposed framework achieves decentralization without inducing entangled dynamics among agents, and it naturally supports multi-objective robotics and real-time implementation. To demonstrate its generality and effectiveness, the framework is applied to three representative problems, namely time-varying leader-follower formation control, decentralized coverage control for time-varying density functions, which is a long-standing open problem, and safe formation navigation in a dense environment.
Systems and Control (eess.SY); Robotics (cs.RO)
arXiv:2511.05900 [eess.SY]
(or arXiv:2511.05900v4 [eess.SY] for this version)
https://doi.org/10.48550/arXiv.2511.05900 Focus to learn more arXiv-issued DOI via DataCite
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