提出可解耦的多智能体控制框架，支持实时与多目标应用。
Disentangled Control of Multi-Agent Systems
- 基于收敛保证的通用框架，实现去中心化控制
- 解决时变密度下的分布式覆盖控制难题
- 适用于动态编队与密集环境安全导航
本文提出一个具有收敛性保障的通用多智能体控制合成框架，适用于广泛问题，包括时变目标函数场景。该框架在实现去中心化的同时避免了智能体间动态耦合，天然支持多目标机器人系统与实时部署。为验证其通用性与有效性，框架应用于三个典型问题：时变领导-跟随编队控制、时变密度函数下的分布式覆盖控制（长期开放难题），以及密集环境中的安全编队导航。
原文摘要 · Abstract (English)
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.
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