用可微服装模拟让机器人精准帮人穿外套
Wearing A Coat: Dual-Arm Robot-Assisted Dressing with Differentiable Clothing Simulation
- 引入可微服装仿真，实时处理衣物与身体的复杂接触
- 支持大时间步稳定计算，实现高频率局部补偿控制
- 在仿真和实物上均验证有效，适合残障人士辅助穿衣
为提升行动不便者的生活质量，发展助穿机器人至关重要。由于穿衣过程中衣物与肢体间存在复杂的接触交互，现有算法多将衣物视为离散片段，难以处理部分已穿衣物的约束条件。为此，本文提出一种新型机器人穿衣控制算法，融合实时可微服装仿真。该仿真采用显式迭代方案，并引入高阶扰动以提升计算效率，同时在大时间步下保持稳定性。通过仿真求解受接触约束的衣物状态，进而实现多阶段控制策略，成功完成外套穿戴。为进一步提升实时性能，设计了带约束的局部模型及其优化求解器，支持对全局控制器的高频局部补偿。最终在仿真与物理场景中均验证了方法的可行性与有效性。
原文摘要 · Abstract (English)
The development of assistive robots for dressing tasks serves to augment human convenience and improve the quality of life for individuals with physical impairments. However, due to the intricate contact interactions between garments and the human limbs during dressing, most robot-assisted dressing algorithms treat clothing as an assembly of discrete segments, thereby struggling to manage the partial worn garments under contact constraints. To overcome this challenge, we propose a novel robotic dressing control algorithm that integrates realtime differentiable clothing simulation. The simulation algorithm employs explicit iterative scheme with intentionally introduced higher-order perturbations to enhance computational efficiency while maintaining stability under large time-step conditions. Through simulation, we resolve the garment state under contact constraints, which then enables a multi-phase control strategy for successful coat dressing assistance. To further improve real-time performance, we introduce a constrained local model along with its corresponding optimization solver, permitting high-frequency local compensation for the differentiable simulation based global controller. Finally, we experimentally validate our approach through both simulated and physical dressing scenarios, conclusively demonstrating its feasibility and efficacy
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