Related papers: Toward a Surgeon-in-the-Loop Ophthalmic Robotic Ap…
Recent advances in machine learning models allowed robots to identify objects on a perceptual nonsymbolic level (e.g., through sensor fusion and natural language understanding). However, these primarily black-box learning models still lack…
Cognitive cooperative assistance in robot-assisted surgery holds the potential to increase quality of care in minimally invasive interventions. Automation of surgical tasks promises to reduce the mental exertion and fatigue of surgeons. In…
In the context of surgery, robots can provide substantial assistance by performing small, repetitive tasks such as suturing, needle exchange, and tissue retraction, thereby enabling surgeons to concentrate on more complex aspects of the…
Automatic laparoscope motion control is fundamentally important for surgeons to efficiently perform operations. However, its traditional control methods based on tool tracking without considering information hidden in surgical scenes are…
The dominant paradigm for end-to-end robot learning focuses on optimizing task-specific objectives that solve a single robotic problem such as picking up an object or reaching a target position. However, recent work on high-capacity models…
Surgical robotics is a rapidly evolving field that is transforming the landscape of surgeries. Surgical robots have been shown to enhance precision, minimize invasiveness, and alleviate surgeon fatigue. One promising area of research in…
Recent advancements in retinal surgery have paved the way for a modern operating room equipped with a surgical robot, a microscope, and intraoperative optical coherence tomography (iOCT)- a depth sensor widely used in retinal surgery.…
Robot-assisted surgery has become progressively more and more popular due to its clinical advantages. In the meanwhile, the artificial intelligence and augmented reality in robotic surgery are developing rapidly and receive lots of…
Surgical robot automation has attracted increasing research interest over the past decade, expecting its potential to benefit surgeons, nurses and patients. Recently, the learning paradigm of embodied intelligence has demonstrated promising…
Reinforcement learning (RL) holds great promise for enabling autonomous acquisition of complex robotic manipulation skills, but realizing this potential in real-world settings has been challenging. We present a human-in-the-loop…
Robot-assisted surgery has revolutionized the healthcare industry by providing surgeons with greater precision, reducing invasiveness, and improving patient outcomes. However, the success of these surgeries depends heavily on the robotic…
Surgical procedures require a high level of technical skill to ensure efficiency and patient safety. Due to the direct effect of surgeon skill on patient outcomes, the development of cost-effective and realistic training methods is…
Robotic skills can be learned via imitation learning (IL) using user-provided demonstrations, or via reinforcement learning (RL) using large amountsof autonomously collected experience.Both methods have complementarystrengths and…
This study presents the first evaluation of general-purpose imitation learning for surgeon-robot collaborative assistance in open surgery, targeting suture following: the grab-pull-release motion an assistant performs at every stitch. We…
Following the technological advancements in medicine, the operation rooms are evolving into intelligent environments. The context-aware systems (CAS) can comprehensively interpret the surgical state, enable real-time warning, and support…
During retinal microsurgery, precise manipulation of the delicate retinal tissue is required for positive surgical outcome. However, accurate manipulation and navigation of surgical tools remain difficult due to a constrained workspace and…
Recent advances in robotic learning in simulation have shown impressive results in accelerating learning complex manipulation skills. However, the sim-to-real gap, caused by discrepancies between simulation and reality, poses significant…
In this study, we present an implementation strategy for a robot that performs peg transfer tasks in Fundamentals of Laparoscopic Surgery (FLS) via imitation learning, aimed at the development of an autonomous robot for laparoscopic…
While robot learning has demonstrated promising results for enabling robots to automatically acquire new skills, a critical challenge in deploying learning-based systems is scale: acquiring enough data for the robot to effectively…
Robotic-assisted procedures offer numerous advantages over traditional approaches, including improved dexterity, reduced fatigue, minimized trauma, and superior outcomes. However, the main challenge of these systems remains the poor…