LAC is presented, a general whole-body controller that simultaneously realizes commanded Linear and Angular Compliance for wrenches applied to the upper body and monotonic modulation over the full range of both stiffness commands, and applicability to teleoperated loco-manipulation tasks.
Abstract
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/
Humanoids are increasingly capable of tracking complex whole-body motions, but physical interaction introduces a different challenge. When a robot makes contact with a person or the environment, it needs to respond to external forces while preserving the motion needed for the task. This response can vary across directi...
Xin-Yuan Luo, Chun-Yuan Yang, Bo-Yuan Chen et al.· 0 citations
Weave is presented, a unified framework for learning whole-body dexterous humanoid-object interaction from captured human demonstrations that converts captured human-object interactions into executable robot-object references through contact-aware retargeting and approach-motion completion.
Liu Cao, Xing-Ze Wu, Jing-Zhi Cui et al.· 2 citations
Embodied AI systems, particularly humanoid robots deployed in real world scenarios require whole-body control policies that are both task-responsive and physically smooth. However, smoothness is not uniform across the body: lower body must remain sufficiently reactive, while the upper body must be tightly regulated to...
Utsav Panchal, Denis Kleyko, Unal Artan et al.· 0 citations
This work presents a gated residual coordination framework that keeps both modules frozen and applies bounded corrections to their outputs, and describes the contributions of reward gating, adaptive correction authority, and separate body and hand correction heads.
Rui Wu, Shuang Li, Li-Ding Zhang et al.· 1 citation
Experimental results demonstrate that a single policy enables a Unitree G1 humanoid to complete the full task using only onboard depth sensing and proprioception, while generalizing robustly across task variations and transferring effectively from simulation to reality.
Ze-Jie Tian, Rui-Bing Hou, Bin Ma et al.· 0 citations
Whole-body compliant control is essential for deploying heavy humanoids under high payload in human-centric environments. Most prior force-aware learning-based pipelines focus on end-effector resistance, per-link upper-body springs, or end-effector stiffness modulation, leaving arbitrary-site perturbations on heavy pla...
Tan-Dzung Do, Cuc T.Trinh, Tuan Dat Phuong et al.· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.