LAC：人形机器人全身控制的线性与角刚度控制

中文摘要 AI 辅助

现实世界的人形机器人任务涉及与物体和人类的物理交互，但当前控制器要么将外力视为干扰而拒绝，要么将刚度控制限制在有限的身体部位，同时忽略角效应。我们提出LAC，一种通用全身控制器，可同时实现施加在上半身的力的指令线性与角刚度控制。首先，我们将全身刚度响应合成为大规模增强数据集，从人类交互数据中提取的接触帧上施加采样的力和力矩事件，在每个接触部位，外力和来自被动柔顺运动链的虚拟力矩在指令刚度下驱动虚拟导纳。随后，师生强化学习训练单一策略以跟踪外力下的刚度运动。最后，大量仿真和现实实验证明，上半身可实现对力的全身刚度响应，在两种刚度指令的全范围内单调调节，且适用于遥操作的运动操作任务。项目网站：this https URL

英文摘要

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/

发表机构

• Tohoku University（东北大学）

机构由 AI 辅助整理，请以论文原文为准。