LapGym-an open source framework for reinforcement learning in robot-assisted laparoscopic surgery
Recent advances in reinforcement learning (RL) have increased the promise of introducing
cognitive assistance and automation to robot-assisted laparoscopic surgery (RALS) …
cognitive assistance and automation to robot-assisted laparoscopic surgery (RALS) …
Gp-vls: A general-purpose vision language model for surgery
Surgery requires comprehensive medical knowledge, visual assessment skills, and
procedural expertise. While recent surgical AI models have focused on solving task-specific …
procedural expertise. While recent surgical AI models have focused on solving task-specific …
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 …
ORBIT-Surgical: An Open-Simulation Framework for Learning Surgical Augmented Dexterity
Physics-based simulations have accelerated progress in robot learning for driving,
manipulation, and locomotion. Yet, a fast, accurate, and robust surgical simulation …
manipulation, and locomotion. Yet, a fast, accurate, and robust surgical simulation …
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 …
Sim2Real Rope Cutting With a Surgical Robot Using Vision-Based Reinforcement Learning
Cutting is a challenging area in the field of autonomous robotics but is especially interesting
for applications such as surgery. One large challenge is the lack of simulations for cutting …
for applications such as surgery. One large challenge is the lack of simulations for cutting …
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 …
Learning Autonomous Surgical Irrigation and Suction with the da Vinci Research Kit Using Reinforcement Learning
The irrigation-suction process is a common procedure to rinse and clean up the surgical
field in minimally invasive surgery (MIS). In this process, surgeons first irrigate liquid …
field in minimally invasive surgery (MIS). In this process, surgeons first irrigate liquid …
A new efficient parallel hierarchical value iteration algorithm using dynamic processor distribution
We consider discounted Markov Decision Processes (MDPs) with large state spaces, aiming
to reduce computational complexity and execution time. Existing hierarchical techniques …
to reduce computational complexity and execution time. Existing hierarchical techniques …
Towards a Physics Engine to Simulate Robotic Laser Surgery: Finite Element Modeling of Thermal Laser-Tissue Interactions
NE Pacheco, K Zhang, AS Reyes, CJ Pacheco… - arxiv preprint arxiv …, 2024 - arxiv.org
This paper presents a computational model, based on the Finite Element Method (FEM), that
simulates the thermal response of laser-irradiated tissue. This model addresses a gap in the …
simulates the thermal response of laser-irradiated tissue. This model addresses a gap in the …