2 citations · 7 across the 11 of their papers we have counts for
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cs.RO2023
Bridging the Sim-to-Real Gap with Dynamic Compliance Tuning for Industrial Insertion
Xiang Zhang, Masayoshi Tomizuka, Hui Li
Contact-rich manipulation tasks often exhibit a large sim-to-real gap. For instance, industrial assembly tasks frequently involve tight insertions where the clearance is less than…
cs.RO2023★ 2 cited
Efficient Sim-to-real Transfer of Contact-Rich Manipulation Skills with Online Admittance Residual Learning
Xiang Zhang, Changhao Wang, Lingfeng Sun +3
Learning contact-rich manipulation skills is essential. Such skills require the robots to interact with the environment with feasible manipulation trajectories and suitable complia…
cs.RO2023
Diff-Transfer: Model-based Robotic Manipulation Skill Transfer via Differentiable Physics Simulation
Yuqi Xiang, Feitong Chen, Qinsi Wang +5
The capability to transfer mastered skills to accomplish a range of similar yet novel tasks is crucial for intelligent robots. In this work, we introduce ,…