6 papers
HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization
Hao Zhang, Yaru Niu, Yikai Wang +2
To improve generalization and resilience in human-robot collaboration (HRC), robots must contend with diverse combinations of human behaviors and contexts, motivating multi-agent r…
Learning Versatile Humanoid Manipulation with Touch Dreaming
Yaru Niu, Zhenlong Fang, Binghong Chen +8
Humanoid robots promise general-purpose assistance, yet real-world humanoid loco-manipulation remains challenging because it requires whole-body stability, end-effector dexterity,…
EMMa: End-Effector Stability-Oriented Mobile Manipulation for Tracked Rescue Robots
Yifei Wang, Hao Zhang, Jidong Huang +2
The autonomous operation of tracked mobile manipulators in rescue missions requires not only ensuring the reachability and safety of robot motion but also maintaining stable end-ef…
ExtremControl: Low-Latency Humanoid Teleoperation with Direct Extremity Control
Ziyan Xiong, Lixing Fang, Junyun Huang +3
Building a low-latency humanoid teleoperation system is essential for collecting diverse reactive and dynamic demonstrations. However, existing approaches rely on heavily pre-proce…
Cognition to Control - Multi-Agent Learning for Human-Humanoid Collaborative Transport
Hao Zhang, Ding Zhao, H. Eric Tseng
Effective human-robot collaboration (HRC) requires translating high-level intent into contact-stable whole-body motion while continuously adapting to a human partner. Many vision-l…
Interaction-Aware Whole-Body Control for Compliant Object Transport
Hao Zhang, Yves Tseng, Ding Zhao +1
Cooperative object transport in unstructured environments remains challenging for assistive humanoids because strong, time-varying interaction forces can make tracking-centric whol…