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Dynamic reconfiguration in multi-robot agent systems using embedded language models
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DOI：10.1016/j.rcim.2026.103308.png)
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Abstract
En 中文
• Natural-language coordination enables flexible control of heterogeneous robots. • Distributed LLM agents support plug-and-play operation without reconfiguration. • AAS provides standardized metadata for skills and live operational state. • RAG retrieves relevant AAS data for adaptive task planning and delegation. • Real robot tests validate dynamic allocation and inter-agent communication.
Keywords:
multi-robot systems
language models
dynamic reconfiguration
agent coordination
adaptive task planning
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