7 papers
PhaForce: Phase-Scheduled Visual-Force Policy Learning with Slow Planning and Fast Correction for Contact-Rich Manipulation
Mingxin Wang, Zhirun Yue, Renhao Lu +7
Contact-rich manipulation requires not only vision-dominant task semantics but also closed-loop reactions to force/torque (F/T) transients. Yet, generative visuomotor policies are…
PMG: Parameterized Motion Generator for Human-like Locomotion Control
Chenxi Han, Yuheng Min, Zihao Huang +4
Recent advances in data-driven reinforcement learning and motion tracking have substantially improved humanoid locomotion, yet critical practical challenges remain. In particular,…
A Step Toward World Models: A Survey on Robotic Manipulation
Peng-Fei Zhang, Ying Cheng, Xiaofan Sun +4
Autonomous agents are increasingly expected to operate in complex, dynamic, and uncertain environments, performing tasks such as manipulation, navigation, and decision-making. Achi…
HL-IK: A Lightweight Implementation of Human-Like Inverse Kinematics in Humanoid Arms
Bingjie Chen, Zihan Wang, Zhe Han +3
Traditional IK methods for redundant humanoid manipulators emphasize end-effector (EE) tracking, frequently producing configurations that are valid mechanically but not human-like.…
MBC: Multi-Brain Collaborative Control for Quadruped Robots
Hang Liu, Yi Cheng, Rankun Li +3
In the field of locomotion task of quadruped robots, Blind Policy and Perceptive Policy each have their own advantages and limitations. The Blind Policy relies on preset sensor inf…
CushionCatch: A Compliant Catching Mechanism for Mobile Manipulators via Combined Optimization and Learning
Bingjie Chen, Keyu Fan, Qi Yang +6
Catching flying objects with a cushioning process is a skill commonly performed by humans, yet it remains a significant challenge for robots. In this paper, we present a framework…