2 citations · 4 across the 7 of their papers we have counts for
8 papers
Bounded Ratio Reinforcement Learning
Yunke Ao, Le Chen, Bruce D. Lee +5
Proximal Policy Optimization (PPO) has become the predominant algorithm for on-policy reinforcement learning due to its scalability and empirical robustness across domains. However…
NeuralBoneReg: An Instance-Specific Label-Free Point Cloud-Based Method for Multi-Modal Bone Surface Registration
Luohong Wu, Matthias Seibold, Nicola A. Cavalcanti +5
In computer- and robot-assisted orthopedic surgery (CAOS), patient-specific surgical plans derived from preoperative imaging define target locations and implant trajectories. Durin…
Robust-Sub-Gaussian Model Predictive Control for Safe Ultrasound-Image-Guided Robotic Spinal Surgery
Yunke Ao, Manish Prajapat, Yarden As +6
Safety-critical control using high-dimensional sensory feedback from optical data (e.g., images, point clouds) poses significant challenges in domains like autonomous driving and r…
SonoGym: High Performance Simulation for Challenging Surgical Tasks with Robotic Ultrasound
Yunke Ao, Masoud Moghani, Mayank Mittal +6
Ultrasound (US) is a widely used medical imaging modality due to its real-time capabilities, non-invasive nature, and cost-effectiveness. Robotic ultrasound can further enhance its…
Stochastic Model Predictive Control for Sub-Gaussian Noise
Yunke Ao, Johannes Köhler, Manish Prajapat +4
We propose a stochastic Model Predictive Control (MPC) framework that ensures closed-loop chance constraint satisfaction for linear systems with general sub-Gaussian process and me…
Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement
Yunke Ao, Hooman Esfandiari, Fabio Carrillo +5
Spinal fusion surgery requires highly accurate implantation of pedicle screw implants, which must be conducted in critical proximity to vital structures with a limited view of anat…
Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning
Yunke Ao, Le Chen, Florian Tschopp +3
Visual-inertial sensors have a wide range of applications in robotics. However, good performance often requires different sophisticated motion routines to accurately calibrate came…
Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning
Le Chen, Yunke Ao, Florian Tschopp +5
Visual-inertial systems rely on precise calibrations of both camera intrinsics and inter-sensor extrinsics, which typically require manually performing complex motions in front of…