1 citations · 1 across the 1 of their papers we have counts for
8 papers
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
SurgiPose: Estimating Surgical Tool Kinematics from Monocular Video for Surgical Robot Learning
Juo-Tung Chen, XinHao Chen, Ji Woong Kim +3
Imitation learning (IL) has shown immense promise in enabling autonomous dexterous manipulation, including learning surgical tasks. To fully unlock the potential of IL for surgery,…
Cosmos-Surg-dVRK: World Foundation Model-based Automated Online Evaluation of Surgical Robot Policy Learning
Lukas Zbinden, Nigel Nelson, Juo-Tung Chen +5
The rise of surgical robots and vision-language-action models has accelerated the development of autonomous surgical policies and efficient assessment strategies. However, evaluati…
SutureBot: A Precision Framework & Benchmark For Autonomous End-to-End Suturing
Jesse Haworth, Juo-Tung Chen, Nigel Nelson +4
Robotic suturing is a prototypical long-horizon dexterous manipulation task, requiring coordinated needle grasping, precise tissue penetration, and secure knot tying. Despite numer…
Surgical Gaussian Surfels: Highly Accurate Real-time Surgical Scene Rendering using Gaussian Surfels
Idris O. Sunmola, Zhenjun Zhao, Samuel Schmidgall +4
Accurate geometric reconstruction of deformable tissues in monocular endoscopic video remains a fundamental challenge in robot-assisted minimally invasive surgery. Although recent…
SRT-H: A Hierarchical Framework for Autonomous Surgery via Language Conditioned Imitation Learning
Ji Woong Kim, Juo-Tung Chen, Pascal Hansen +11
Research on autonomous surgery has largely focused on simple task automation in controlled environments. However, real-world surgical applications demand dexterous manipulation ove…