让仿人机器人全身在受力时同时实现线性和角向柔顺响应
LAC: Linear and Angular Compliance for Humanoid Whole-body Control
- 构建大规模数据集，模拟人体交互中的受力与虚拟扭矩协同作用
- 通过强化学习训练单一策略，实现上半身全范围柔顺性调节
- 适用于远程操控的抓取与移动任务，真实场景验证效果
现实世界中的仿人机器人需与物体和人类进行物理交互，但现有控制器要么将外部力视为干扰，要么仅限制部分肢体的柔顺性，忽略角向效应。本文提出LAC，一种通用全身控制器，可同时实现对上半身所受力矩和力的线性和角向柔顺控制。首先，基于人体交互数据提取接触位姿，合成大规模增强数据集，施加采样的力和力偶事件。在每个接触链上，外部力与被动柔顺运动链产生的虚拟扭矩共同驱动虚拟导纳，服从设定刚度。随后，采用教师-学生强化学习训练单一策略，以追踪外力作用下的柔顺运动。大量仿真与真实实验表明，该方法能实现上半身对力矩和力的全身柔顺响应，且刚度命令在全范围内单调可调，并成功应用于远程操控的移物与行走任务。
原文摘要 · Abstract (English)
Real-world humanoid tasks involve physical interaction with objects and humans, yet current controllers either reject external forces as disturbances or restrict compliance to limited body links while ignoring angular effects. We present LAC, a general whole-body controller that simultaneously realizes commanded Linear and Angular Compliance for wrenches applied to the upper body. First, we synthesize whole-body compliant responses into a large-scale augmented dataset. Sampled force and couple events are imposed on contact frames extracted from human interaction data. At each contact link, the external force and a virtual torque from the passively yielding kinematic chain drive a virtual admittance under the commanded stiffness. Subsequently, teacher-student reinforcement learning trains a single policy to track the compliant motions under external wrenches. Finally, extensive simulation and real-world experiments demonstrate whole-body compliant responses to wrenches across the upper body, monotonic modulation over the full range of both stiffness commands, and applicability to teleoperated loco-manipulation tasks. Project website: https://lac-humanoid.github.io/
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