外观
论文arXiv 2610.1991314 天前
MUCO：面向组合式长时程机器人任务的 Mani-Unit 结构化操作框架
原文链接：MUCO: A Mani-Unit-Structured Manipulation Framework for Compositional Long-Horizon Robot Tasks（arXiv 2610.19913 · 发布日期：2026-10-14）
MUCO: A Mani-Unit-Structured Manipulation Framework for Compositional Long-Horizon Robot Tasks
MUCO以可复用操作单元编排长时程操作，基于语言视觉选择策略，并在RLBench、RoboTwin 2.0和真实任务验证。
核心要点
- 完整轨迹学习长时程操作会增加数据成本、限制能力复用，并使局部失败向后续阶段传播。
- 方法将操作单元定义为含局部目标、启动条件及可观察成败标准的可复用操作，并逐个学习与验证。
- 执行时，MUCO依据语言和视觉构建操作单元序列，从冻结能力库匹配策略并按校准成功率调度。
- 在RLBench、RoboTwin 2.0和五个真实任务上，相比基线提高完整任务成功、已验证进展并降低错误传播。
验证范围与局限：验证范围为RLBench、RoboTwin 2.0和五个真实世界任务。
英文摘要 (Abstract)
Learning and executing long-horizon robot manipulation as complete task trajectories raises data-collection costs, lim?its capability reuse, and causes local failures to cascade into later task stages. We introduce manipulation units (MUs) as reusable operations, each defined by a local goal, an initi?ation condition, and observable success and failure criteria. MUs are learned and verified individually. During execution, consecutive MUs remain coupled through shared environ?ment dynamics. We formulate MU-Structured Manipulation (MUSM) and realize it through MU-Centric Orchestration (MUCO). Given language and vision, MUCO constructs an MU sequence, matches each MU to compatible policy models in a frozen capability registry, and dispatches the model with the highest calibrated success rate. Visual verification checks MU outcomes against success and failure criteria and governs transitions, enabling retry or fallback to another model from the current state without re-executing verified MUs. Canonical keys enable checkpoint reuse for equivalent MUs across tasks without new demonstrations or updates. We evaluate MUCO on RLBench, RoboTwin 2.0, and five real-world tasks. MUCO achieves higher complete-task success and verified progress, stronger failure containment, and lower error propagation than baselines. Results demonstrate cross-task MU reuse and het?erogeneous policy composition without joint training, shared backbones, or common action representations.
作者：Xiangyi Wei, Hanzhe Yao, Jingwen Shang, Zhenhong Wu, Yang Li, Changbo Wang
来源
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