9 citations · 17 across the 4 of their papers we have counts for
6 papers
Intermittent Visual Servoing: Efficiently Learning Policies Robust to Instrument Changes for High-precision Surgical Manipulation
Samuel Paradis, Minho Hwang, Brijen Thananjeyan +6
Automation of surgical tasks using cable-driven robots is challenging due to backlash, hysteresis, and cable tension, and these issues are exacerbated as surgical instruments must…
Untangling Dense Knots by Learning Task-Relevant Keypoints
Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan +7
Untangling ropes, wires, and cables is a challenging task for robots due to the high-dimensional configuration space, visual homogeneity, self-occlusions, and complex dynamics. We…
Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics
Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan +10
Robotic fabric manipulation is challenging due to the infinite dimensional configuration space, self-occlusion, and complex dynamics of fabrics. There has been significant prior wo…
Efficiently Calibrating Cable-Driven Surgical Robots with RGBD Fiducial Sensing and Recurrent Neural Networks
Minho Hwang, Brijen Thananjeyan, Samuel Paradis +5
Automation of surgical subtasks using cable-driven robotic surgical assistants (RSAs) such as Intuitive Surgical's da Vinci Research Kit (dVRK) is challenging due to imprecision in…
Applying Depth-Sensing to Automated Surgical Manipulation with a da Vinci Robot
Minho Hwang, Daniel Seita, Brijen Thananjeyan +5
Recent advances in depth-sensing have significantly increased accuracy, resolution, and frame rate, as shown in the 1920x1200 resolution and 13 frames per second Zivid RGBD camera.…
Deep Imitation Learning of Sequential Fabric Smoothing From an Algorithmic Supervisor
Daniel Seita, Aditya Ganapathi, Ryan Hoque +11
Sequential pulling policies to flatten and smooth fabrics have applications from surgery to manufacturing to home tasks such as bed making and folding clothes. Due to the complexit…