2 citations · 3 across the 2 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…
Towards Robust Surgical Automation via Digital Twin Representations from Foundation Models
Hao Ding, Lalithkumar Seenivasan, Hongchao Shu +7
Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning complex action sequences. Sound plann…
Towards Dynamic Model Identification and Gravity Compensation for the dVRK-Si Patient Side Manipulator
Haoying Zhou, Hao Yang, Brendan Burkhart +5
The da Vinci Research Kit (dVRK) is widely used for research in robot-assisted surgery, but most modeling and control methods target the first-generation dVRK Classic. The recently…
SurgSync: Time-Synchronized Multi-Modal Data Collection Framework and Dataset for Surgical Robotics
Haoying Zhou, Chang Liu, Yimeng Wu +7
Most existing robotic surgery systems adopt a human-in-the-loop paradigm, often with the surgeon directly teleoperating the robotic system. Adding intelligence to these robots woul…
SurgPose: a Dataset for Articulated Robotic Surgical Tool Pose Estimation and Tracking
Zijian Wu, Adam Schmidt, Randy Moore +4
Accurate and efficient surgical robotic tool pose estimation is of fundamental significance to downstream applications such as augmented reality (AR) in surgical training and learn…
Gravity Compensation of the dVRK-Si Patient Side Manipulator based on Dynamic Model Identification
Haoying Zhou, Hao Yang, Anton Deguet +3
The da Vinci Research Kit (dVRK, also known as dVRK Classic) is an open-source teleoperated surgical robotic system whose hardware is obtained from the first generation da Vinci Su…