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English(EN) Scale-Plan: Scalable Language-Enabled Task Planning for Heterogeneous Multi-Robot Teams

Scale-Plan框架借助LLM辅助增强多机器人任务规划

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了Scale-Plan，一个旨在增强异构多机器人团队任务规划的新框架。该系统利用大型语言模型（LLMs）从自然语言指令中创建简洁、与任务相关的问��表示，过滤掉不相关的信息。Scale-Plan构建动作图，并采用由LLM推理引导的结构化搜索来识别关键动作和对象，从而提高复杂环境中的可扩展性和可靠性。在新构建于AI2-THOR之上的MAT2-THOR基准测试中的评估表明，Scale-Plan的性能优于现有的LLM和混合LLM-PDDL规划方法。 AI

影响 该框架可以实现多机器人系统在复杂、现实场景中更高效、更可靠的部署。

排序理由 该集群包含一篇详细介绍机器人新框架的学术论文。[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 →

Scale-Plan框架借助LLM辅助增强多机器人任务规划

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该集群包含一篇详细介绍机器人新框架的学术论文。[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) · Piyush Gupta, Sangjae Bae, Jiachen Li, David Isele ·

    Scale-Plan：异构多机器人团队的可扩展语言驱动任务规划

    arXiv:2603.08814v2 Announce Type: replace-cross Abstract: Long-horizon task planning for heterogeneous multi-robot systems is essential for deploying collaborative teams in real-world environments; yet, it remains challenging due to the large volume of perceptual information, muc…

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