10 citations · 13 across the 7 of their papers we have counts for
4 papers · 1 filter
Reward Learning from Suboptimal Demonstrations with Applications in Surgical Electrocautery
Zohre Karimi, Shing-Hei Ho, Bao Thach +2
Automating robotic surgery via learning from demonstration (LfD) techniques is extremely challenging. This is because surgical tasks often involve sequential decision-making proces…
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…
General-purpose foundation models for increased autonomy in robot-assisted surgery
Samuel Schmidgall, Ji Woong Kim, Alan Kuntz +2
The dominant paradigm for end-to-end robot learning focuses on optimizing task-specific objectives that solve a single robotic problem such as picking up an object or reaching a ta…