4 citations · 4 across the 8 of their papers we have counts for
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cs.RO2024
Should We Learn Contact-Rich Manipulation Policies from Sampling-Based Planners?
Huaijiang Zhu, Tong Zhao, Xinpei Ni +4
The tremendous success of behavior cloning (BC) in robotic manipulation has been largely confined to tasks where demonstrations can be effectively collected through human teleopera…
cs.RO2024
Planning-Guided Diffusion Policy Learning for Generalizable Contact-Rich Bimanual Manipulation
Xuanlin Li, Tong Zhao, Xinghao Zhu +3
Contact-rich bimanual manipulation involves precise coordination of two arms to change object states through strategically selected contacts and motions. Due to the inherent comple…
cs.RO2024★ 4 cited
Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans?
Yuki Shirai, Tong Zhao, H. J. Terry Suh +5
Designing planners and controllers for contact-rich manipulation is extremely challenging as contact violates the smoothness conditions that many gradient-based controller synthesi…