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New decentralized MPC framework ensures safety in multi-agent systems

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new decentralized model predictive control (MPC) framework for multi-agent systems that operates under state-only information and limited sensing. This approach ensures recursive feasibility, safety, and Lyapunov-type convergence by utilizing agent-wise fallback regions. The system allows for less conservative decentralized interaction and memory-free local handling of neighbors, even with finite sensing ranges, preserving the core contingency MPC structure. AI

IMPACT This research could lead to more robust and safer autonomous systems operating in complex, multi-agent environments.

RANK_REASON The cluster contains an academic paper detailing a new control framework for multi-agent systems. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New decentralized MPC framework ensures safety in multi-agent systems

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The cluster contains an academic paper detailing a new control framework for multi-agent systems. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Georg Schildbach ·

    Provably Safe Decentralized Contingency MPC under State-Only Information and Limited Sensing for Nonlinear Multi-agent Systems

    This paper considers decentralized contingency MPC for multi-agent control under a state-only information pattern, with particular focus on limited sensing and plug-and-play operation. The objective is to retain recursive feasibility, safety, and Lyapunov-type convergence while r…

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