2 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
Early Failure Detection in Autonomous Surgical Soft-Tissue Manipulation via Uncertainty Quantification
Jordan Thompson, Ronald Koe, Anthony Le +3
Autonomous surgical robots are a promising solution to the increasing demand for surgery amid a shortage of surgeons. Recent work has proposed learning-based approaches for the aut…
Modeling Kinematic Uncertainty of Tendon-Driven Continuum Robots via Mixture Density Networks
Jordan Thompson, Brian Y. Cho, Daniel S. Brown +1
Tendon-driven continuum robot kinematic models are frequently computationally expensive, inaccurate due to unmodeled effects, or both. In particular, unmodeled effects produce unce…
Accounting for Hysteresis in the Forward Kinematics of Nonlinearly-Routed Tendon-Driven Continuum Robots via a Learned Deep Decoder Network
Brian Y. Cho, Daniel S. Esser, Jordan Thompson +3
Tendon-driven continuum robots have been gaining popularity in medical applications due to their ability to curve around complex anatomical structures, potentially reducing the inv…