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cs.RO2024
EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents
Junting Chen, Checheng Yu, Xunzhe Zhou +7
Heterogeneous multi-robot systems (HMRS) have emerged as a powerful approach for tackling complex tasks that single robots cannot manage alone. Current large-language-model-based m…
cs.RO2024★ 2 cited
Learning Reward for Robot Skills Using Large Language Models via Self-Alignment
Yuwei Zeng, Yao Mu, Lin Shao
Learning reward functions remains the bottleneck to equip a robot with a broad repertoire of skills. Large Language Models (LLM) contain valuable task-related knowledge that can po…