Surgical Gym: A high-performance GPU-based platform for reinforcement learning with surgical robots
S Schmidgall, A Krieger… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Recent advances in robot-assisted surgery have resulted in progressively more precise,
efficient, and minimally invasive procedures, sparking a new era of robotic surgical …
efficient, and minimally invasive procedures, sparking a new era of robotic surgical …
Movement primitive diffusion: Learning gentle robotic manipulation of deformable objects
Policy learning in robot-assisted surgery (RAS) lacks data efficient and versatile methods
that exhibit the desired motion quality for delicate surgical interventions. To this end, we …
that exhibit the desired motion quality for delicate surgical interventions. To this end, we …
Autonomous Blood Suction for Robot-Assisted Surgery: A Sim-to-Real Reinforcement Learning Approach
Recent applications of deep reinforcement learning (DRL) in surgical autonomy have shown
promising results in automating various surgical sub-tasks. While most of these studies …
promising results in automating various surgical sub-tasks. While most of these studies …
Real-to-sim deformable object manipulation: Optimizing physics models with residual mappings for robotic surgery
Accurate deformable object manipulation (DOM) is essential for achieving autonomy in
robotic surgery, where soft tissues are being displaced, stretched, and dissected. Many DOM …
robotic surgery, where soft tissues are being displaced, stretched, and dissected. Many DOM …
Integrating human learning and reinforcement learning: A novel approach to agent training
YH Li, F Zhang, Q Hua, XH Zhou - Knowledge-Based Systems, 2024 - Elsevier
Off-policy reinforcement learning (RL) algorithms are known for improving sample efficiency
by employing prior experiences in experience replay memory. However, most existing off …
by employing prior experiences in experience replay memory. However, most existing off …
A Multiarm Robotic Platform for Scientific Exploration: Its Design, Digital Twins, and Validation
MM Marinho, JJ Quiroz-Omaña… - IEEE Robotics & …, 2024 - ieeexplore.ieee.org
There is a large number of robotic platforms with two or more arms targeting surgical
applications. Despite that, very few groups have employed such platforms for scientific …
applications. Despite that, very few groups have employed such platforms for scientific …
[PDF][PDF] Robot Learning Incorporating Human Interventions in the Real World for Autonomous Surgical Endoscopic Camera Control.
Recent studies in surgical robotics have focused on automating common surgical subtasks
such as grasping and manipulation using deep reinforcement learning (DRL). In this work …
such as grasping and manipulation using deep reinforcement learning (DRL). In this work …
Efficient Physically-based Simulation of Soft Bodies in Embodied Environment for Surgical Robot
Surgical robot simulation platform plays a crucial role in enhancing training efficiency and
advancing research on robot learning. Much effort have been made by scholars on …
advancing research on robot learning. Much effort have been made by scholars on …
SurgicAI: A Fine-grained Platform for Data Collection and Benchmarking in Surgical Policy Learning
Despite advancements in robotic-assisted surgery, automating complex tasks like suturing
remain challenging due to the need for adaptability and precision. Learning-based …
remain challenging due to the need for adaptability and precision. Learning-based …
From Decision to Action in Surgical Autonomy: Multi-Modal Large Language Models for Robot-Assisted Blood Suction
The rise of Large Language Models (LLMs) has impacted research in robotics and
automation. While progress has been made in integrating LLMs into general robotics tasks …
automation. While progress has been made in integrating LLMs into general robotics tasks …