output
20212026
most citedSynthesizing Diverse and Physically Stable Grasps with Arbitrary Hand Structures using Differentiable Force Closure Estimator

91 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2024 · cs.ROShow all

5 papers · 2 filters

cs.RO2024★ 64 cited

Embedding high-resolution touch across robotic hands enables adaptive human-like grasping

Zihang Zhao, Wanlin Li, Yuyang Li +9

Developing robotic hands that adapt to real-world dynamics remains a fundamental challenge in robotics and machine intelligence. Despite significant advances in replicating human h…

cs.RO2024★ 14 cited

M2Diffuser: Diffusion-based Trajectory Optimization for Mobile Manipulation in 3D Scenes

Sixu Yan, Zeyu Zhang, Muzhi Han +7

Recent advances in diffusion models have opened new avenues for research into embodied AI agents and robotics. Despite significant achievements in complex robotic locomotion and sk…

cs.RO2024★ 17 cited

MiniTac: An Ultra-Compact 8 mm Vision-Based Tactile Sensor for Enhanced Palpation in Robot-Assisted Minimally Invasive Surgery

Wanlin Li, Zihang Zhao, Leiyao Cui +4

Robot-assisted minimally invasive surgery (RAMIS) provides substantial benefits over traditional open and laparoscopic methods. However, a significant limitation of RAMIS is the su…

cs.RO2024

M3Bench: Benchmarking Whole-body Motion Generation for Mobile Manipulation in 3D Scenes

Zeyu Zhang, Sixu Yan, Muzhi Han +4

We propose M3Bench, a new benchmark for whole-body motion generation in mobile manipulation tasks. Given a 3D scene context, M3Bench requires an embodied agent to reason about its…

cs.RO2024★ 20 cited

Tac-Man: Tactile-Informed Prior-Free Manipulation of Articulated Objects

Zihang Zhao, Yuyang Li, Wanlin Li +4

Integrating robots into human-centric environments such as homes, necessitates advanced manipulation skills as robotic devices will need to engage with articulated objects like doo…