4 citations · 4 across the 6 of their papers we have counts for
3 papers · 1 filter
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…
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…
Diffusion-based learning of contact plans for agile locomotion
Victor Dhédin, Adithya Kumar Chinnakkonda Ravi, Armand Jordana +5
Legged robots have become capable of performing highly dynamic maneuvers in the past few years. However, agile locomotion in highly constrained environments such as stepping stones…