Robot-assistive minimally invasive surgery:trends and future directions

The evolution of medical technologies—such as surgical devices and imaging techniques—has transformed all aspects of surgery. A key area of development is robot-assisted minimally invasive surgery (MIS). This review paper provides an overview of the evolution of robotic MIS, from its infancy to our days, and envisioned future challenges. It provides an outlook of breakthrough surgical robotic platforms, their clinical applications, and their evolution over the years. It discusses how the integration of robotic, imaging, and sensing technologies has contributed to create novel surgical platforms that can provide the surgeons with enhanced dexterity, precision, and surgical navigation while reducing the invasiveness and efficacy of the intervention. Finally, this review provides an outlook on the future of robotic MIS discussing opportunities and challenges that the scientific community will have to address in the coming decade. We hope that this review serves to provide a quick and accessible way to introduce the readers to this exciting and fast-evolving area of research, and to inspire future research in this field

Soft Robot-Assisted Minimally Invasive Surgery and Interventions: Advances and Outlook

Since the emergence of soft robotics around two decades ago, research interest in the field has escalated at a pace. It is fuelled by the industry's appreciation of the wide range of soft materials available that can be used to create highly dexterous robots with adaptability characteristics far beyond that which can be achieved with rigid component devices. The ability, inherent in soft robots, to compliantly adapt to the environment, has significantly sparked interest from the surgical robotics community. This article provides an in-depth overview of recent progress and outlines the remaining challenges in the development of soft robotics for minimally invasive surgery

Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons

Enabling the future of colonoscopy with intelligent and autonomous magnetic manipulation

Early diagnosis of colorectal cancer substantially improves survival. However, over half of cases are diagnosed late due to the demand for colonoscopy—the ‘gold standard’ for screening—exceeding capacity. Colonoscopy is limited by the outdated design of conventional endoscopes, which are associated with high complexity of use, cost and pain. Magnetic endoscopes are a promising alternative and overcome the drawbacks of pain and cost, but they struggle to reach the translational stage as magnetic manipulation is complex and unintuitive. In this work, we use machine vision to develop intelligent and autonomous control of a magnetic endoscope, enabling non-expert users to effectively perform magnetic colonoscopy in vivo. We combine the use of robotics, computer vision and advanced control to offer an intuitive and effective endoscopic system. Moreover, we define the characteristics required to achieve autonomy in robotic endoscopy. The paradigm described here can be adopted in a variety of applications where navigation in unstructured environments is required, such as catheters, pancreatic endoscopy, bronchoscopy and gastroscopy. This work brings alternative endoscopic technologies closer to the translational stage, increasing the availability of early-stage cancer treatments

Mobility, Navigation and Localization Towards Robotic Endoscopy

With significant progress being made towards improving endoscope technology such as capsule endoscopy and robotic endoscopy, the development of advanced strategies for manipulating, controlling and more generally, easing the accessibility of these devices for physicians is an important next step. This work presents the development of several robotic platforms for experimentally testing navigation and localization strategies in robotic endoscopy followed by the development and testing of navigation strategies using these devices. Finally, visual and visual inertial localization and mapping is explored on two of these robotic systems. We first present a detailed description on the state-of-the-art with regard to minimally invasive robotic surgery and then follow this with in-depth description of our design and validation of two important systems, the Robotic Endoscope Platform (REP) and the Modular Endoscopy Simulation Apparatus (MESA), for exploring some of the challenges in robotic endoscopy. Following these descriptions we present a technique for autonomous navigation of the REP within the MESA as well as an attempt at applying Simultaneous Localization and Mapping (SLAM) to allow for the real-time localization of this system. Finally, we transition these techniques to the Endoculus, a complete robotic endoscope suitable for in vivo testing, and demonstrate both autonomous navigation for this device, and the implementation of three different SLAM systems for localization and mapping of the Endoculus system in real-time. Throughout these experiments we demonstrate the potential for advanced methods in computer vision along with other sensory techniques to substantially benefit endoscopy, enabling greater and greater autonomy of these systems and furthering the case for robotic endoscopy as a whole.</p

Frontiers of robotic endoscopic capsules: a review

Digestive diseases are a major burden for society and healthcare systems, and with an aging population, the importance of their effective management will become critical. Healthcare systems worldwide already struggle to insure quality and affordability of healthcare delivery and this will be a significant challenge in the midterm future. Wireless capsule endoscopy (WCE), introduced in 2000 by Given Imaging Ltd., is an example of disruptive technology and represents an attractive alternative to traditional diagnostic techniques. WCE overcomes conventional endoscopy enabling inspection of the digestive system without discomfort or the need for sedation. Thus, it has the advantage of encouraging patients to undergo gastrointestinal (GI) tract examinations and of facilitating mass screening programmes. With the integration of further capabilities based on microrobotics, e.g. active locomotion and embedded therapeutic modules, WCE could become the key-technology for GI diagnosis and treatment. This review presents a research update on WCE and describes the state-of-the-art of current endoscopic devices with a focus on research-oriented robotic capsule endoscopes enabled by microsystem technologies. The article also presents a visionary perspective on WCE potential for screening, diagnostic and therapeutic endoscopic procedures