外观
论文arXiv 2609.3804629 天前
EgoAlign：弥合长距离移动操作中的人类-人形机器人鸿沟
原文链接：EgoAlign: Bridging the Human-Humanoid Gap for Long-Range Loco-Manipulation（arXiv 2609.38046 · 发布日期：2026-09-29）
EgoAlign: Bridging the Human-Humanoid Gap for Long-Range Loco-Manipulation
EgoAlign将第一视角人类示教转为人形机器人全身控制监督，并通过微调视觉-语言-动作模型在物理人形机器人上验证。
核心要点
- 第一视角人类示教易获取，但尺度、控制响应差异和缺失机器人状态限制其监督价值。
- 方法用目标机器人模型与仿真器引导采集，并结合尺度对齐和控制器在环细化上身交互。
- 因果回放重建机器人状态与运动标记，用适配后人类示教微调视觉-语言-动作模型。
- 零样本部署完成长距离物体搬移、未见目标导航和足部交互；细化优于单纯运动学对齐。
验证范围与局限：验证包括仿真手部对齐评估，以及在一台物理人形机器人上的零样本部署任务。
英文摘要 (Abstract)
Egocentric human demonstrations offer an accessible source of task experience, but differences in body scale and controller response, together with missing robot states, limit their value as humanoid training supervision. We present EgoAlign, a data-construction framework that converts these demonstrations into action and state supervision compatible with a general-purpose, continuous whole-body controller, without collecting physical-robot demonstrations. Using the target-robot model and simulator, EgoAlign guides demonstration collection through execution feedback. It preserves locomotion references for visually guided periodic stepping while adapting upper-body interaction geometry through scale alignment and controller-in-the-loop refinement. A final causal replay reconstructs the corresponding robot states and motion-token labels for training with the human observations. We assess the resulting supervision by fine-tuning a vision--language--action model solely on adapted human demonstrations and deploying it zero-shot on a physical humanoid. The resulting policies perform long-range object relocation, navigation to unseen goal positions, and independently evaluated foot interaction. Refinement improves simulated hand alignment and physical pickup success over kinematic alignment alone, while human collection reduces on-site acquisition time relative to teleoperation. https://lambdahumanoid.github.io/EgoAlign/
作者：Yiming Jiang, Jin Chen, Chongyang Xu, Yilun Chen, Hao Aimin, Yisheng He
来源
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