20 citations · 22 across the 4 of their papers we have counts for
6 papers
STITCH 2.0: Extending Augmented Suturing with EKF Needle Estimation and Thread Management
Kush Hari, Ziyang Chen, Hansoul Kim +1
Surgical suturing is a high-precision task that impacts patient healing and scarring. Suturing skill varies widely between surgeons, highlighting the need for robot assistance. Pre…
STITCH: Augmented Dexterity for Suture Throws Including Thread Coordination and Handoffs
Kush Hari, Hansoul Kim, Will Panitch +6
We present STITCH: an augmented dexterity pipeline that performs Suture Throws Including Thread Coordination and Handoffs. STITCH iteratively performs needle insertion, thread swee…
Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones
Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair +7
Safety remains a central obstacle preventing widespread use of RL in the real world: learning new tasks in uncertain environments requires extensive exploration, but safety require…
Constraint Estimation and Derivative-Free Recovery for Robot Learning from Demonstrations
Jonathan Lee, Michael Laskey, Roy Fox +1
Learning from human demonstrations can facilitate automation but is risky because the execution of the learned policy might lead to collisions and other failures. Adding explicit c…
Using Intermittent Synchronization to Compensate for Rhythmic Body Motion During Autonomous Surgical Cutting and Debridement
Vatsal Patel, Sanjay Krishnan, Aimee Goncalves +3
Anatomical structures are rarely static during a surgical procedure due to breathing, heartbeats, and peristaltic movements. Inspired by observing an expert surgeon, we propose an…
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations
Michael Laskey, Caleb Chuck, Jonathan Lee +5
Motivated by recent advances in Deep Learning for robot control, this paper considers two learning algorithms in terms of how they acquire demonstrations. "Human-Centric" (HC) samp…