5 citations · 5 across the 12 of their papers we have counts for
9 papers · 1 filter
MACAW: Reliable And Efficient Surgical Debridement Using Monocular Adaptive Compact Attention Windows
Ziyang Chen, Shutong Jin, Preethi Satish +6
Augmenting the dexterity of human surgeons has the potential to free them from tedious subtasks. We consider debridement (removal of diseased or dead tissue fragments), which is ch…
Adversarial Attacks on Learned Policies for Surgical Robotic Tasks
Shutong Jin, Ziyang Chen, Preethi Satish +3
Learning-based policies are being considered to augment the dexterity of human surgeons in robot-assisted surgery. Can the end-to-end mapping from visual observations to robot acti…
Speculative Policy Orchestration: A Latency-Resilient Framework for Cloud-Robotic Manipulation
Chanh Nguyen, Shutong Jin, Florian T. Pokorny +1
Cloud robotics enables robots to offload high-dimensional motion planning and reasoning to remote servers. However, for continuous manipulation tasks requiring high-frequency contr…
RoboLight: A Dataset with Linearly Composable Illumination for Robotic Manipulation
Shutong Jin, Jin Yang, Muhammad Zahid +1
In this paper, we introduce RoboLight, the first real-world robotic manipulation dataset capturing synchronized episodes under systematically varied lighting conditions. RoboLight…
Physically-based Lighting Generation for Robotic Manipulation
Shutong Jin, Lezhong Wang, Ben Temming +1
In this paper, we propose the first framework that leverages physically-based inverse rendering for novel lighting generation on existing real-world human demonstrations of robotic…
R900: Understanding the Cost-Effectiveness of Random Exploration from 900 Hours of Robotic Data Collection
Shutong Jin, Axel Kaliff, Ruiyu Wang +2
Data scarcity presents a key bottleneck for imitation learning in robotic manipulation. In this paper, we focus on random exploration data-actions and video sequences produced auto…