外观
论文arXiv 2609.047591 个月前
运动中穿衣：一种用于机器人辅助穿衣的人体运动感知 Diffusion Policy
原文链接：Dressing in Motion: A Human Motion-Aware Diffusion Policy for Robot-Assisted Dressing（arXiv 2609.04759 · 发布日期：2026-09-04）
Dressing in Motion: A Human Motion-Aware Diffusion Policy for Robot-Assisted Dressing
该文面向用户手臂运动下的机器人辅助穿衣，提出基于点云与PDE扩散表征的Diffusion Policy，并在仿真和真人研究中验证。
核心要点
- 用户运动时，衣物—人体接触和遮挡复杂，难以生成与手臂运动对齐的动作。
- 方法从静态专家示范学习，利用部分观测点云和面向交互几何的Diffusion Policy。
- 引入基于PDE扩散的物体中心表征，采样并配准运动相关区域以反应式调整轨迹。
- 实验显示在穿衣进展、运动自由度和用户舒适度上优于基线，并提供项目网站。
验证范围与局限：验证范围包括仿真，以及9名参与者、3类衣物和6种手臂运动模式的真实人体研究。
英文摘要 (Abstract)
Robotic dressing assistance is a promising solution for supporting older adults with physical impairments in daily living. However, dressing under human motion remains challenging, as complex garment--human contact and occlusions make it difficult to generate actions aligned with arm movements. In this letter, we propose a visuomotor policy that learns dressing skills from static expert demonstrations and generalizes to dynamic user-motion scenarios. A diffusion policy tailored to garment--human interaction geometry learns from partially observed point clouds with varied arm postures. We then introduce an object-centric representation based on PDE diffusion to capture the axial distribution of the arm. By sampling motion-relevant regions and registering them across consecutive observations, the proposed method approximates arm motion and reactively adapts the executed trajectory. We evaluate our method in simulation and a real-world human study involving nine participants, three garment types, and six arm-motion patterns. Results show that our method outperforms baselines in dressing progress, freedom of movement, and user comfort. The project website is https://anonymous.4open.science/w/dressing-in-motion.
作者：Haoxiang Sun, Fangyuan Wang, Songhao Huang, Justina Y. W. Liu, Jihong Zhu, Peng Zhou, David Navarro-Alarcón
来源
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