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English(EN) EmboTeam: Asymmetric State Grounding for Heterogeneous Multi-Robot Collaboration

EmboTeam框架利用LLM和PDDL增强多机器人协作

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了EmboTeam，一个神经符号框架，旨在提高异构多机器人系统在长时间内的协作能力。该框架集成了大型语言模型进行任务规划，并结合使用规划领域定义语言（PDDL）进行状态验证和协调的符号搜索。EmboTeam提高了任务成功率和目标条件召回率，在复杂的多机器人场景中优于之前的LaMMA-P等方法。 AI

影响 该框架可以提高需要长期协调的任务中复杂机器人系统的效率和可靠性。

排序理由 该集群包含一篇详细介绍多机器人协作新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

EmboTeam框架利用LLM和PDDL增强多机器人协作

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该集群包含一篇详细介绍多机器人协作新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Haishan Zeng, Mengna Wang, Peng Li ·

    EmboTeam：异构多机器人协作的不对称状态对齐

    arXiv:2601.11063v3 Announce Type: replace-cross Abstract: Heterogeneous multi-robot collaboration over long horizons requires both global task planning and robust coordination during execution. Existing plan- ners using large language models (LLMs) can generate task decomposition…

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