1 citations · 1 across the 3 of their papers we have counts for
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World Models for Robotic Manipulation: A Survey
Fangyuan Wang, Ziyuan Wang, Guorui Pei +15
Robotic manipulation depends on the ability to anticipate how actions reshape objects, contacts, and scene geometry before execution. Learned world models provide this capability b…
Learning a Kinodynamic Trajectory Manifold for Impact-Aware Compliant Catching of Fast-Moving Objects
Guorui Pei, Mengshi Zhang, Xi Chen +3
Fast catching of free-flying objects is difficult because of short reaction time, impact uncertainty, and kinodynamic constraints. We use reinforcement learning in simulation to co…
Failure-Aware Bimanual Teleoperation via Conservative Value Guided Assistance
Peng Zhou, Zhongxuan Li, Jinsong Wu +7
Teleoperation of high-precision manipulation is con-strained by tight success tolerances and complex contact dy-namics, which make impending failures difficult for human operators…
Learning Rhythmic Trajectories with Geometric Constraints for Laser-Based Skincare Procedures
Anqing Duan, Wanli Liuchen, Jinsong Wu +3
The increasing deployment of robots has significantly enhanced the automation levels across a wide and diverse range of industries. This paper investigates the automation challenge…