arXiv 2610.29560 · cs.RO · 2026-10-21
From VLM Planners to Robotic Agents: Self-Evolving Harnesses for History-Dependent Manipulation
Tingwen Du, Haoyu Guo, Hanxue Zhang, Xuanxu Wang, Junting Dong, Chao Gao, Mingfei Han, Tao Lu 等 12 人
机构待核实
在最新榜 #324 本站收录于 2026-10-24
一句话要点
这篇论文研究依赖历史的长程机器人操作:任务进度和过往交互结果需要记住,部分可观测和执行错误会累积;作者把高层视觉语言模型组织成带记忆、能自我演化的执行框架来规划,配合底层动作执行。
This paper targets history-dependent, long-horizon robot manipulation where task progress and past outcomes must be retained and errors compound; it organizes the high-level VLM planner into a self-evolving harness with memory on top of low-level action execution.
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数据说明
元数据来自 arXiv API(已核实);点赞来自 Hugging Face 每日论文;引用来自 Semantic Scholar。最近刷新 2026-10-26。
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