140 research outputs found

    Design of a Robotic Instrument Manipulator for Endoscopic Deployment

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    This thesis describes the initial design process for an application of continuum robotics to endoscopic surgical procedures, specifically dissection of the colon. We first introduce the long-term vision for a benchtop dual-instrument endoscopic system with intuitive haptic controllers and then narrow our focus to the design and testing of the instrument manipulator itself, which must be actuated through the long, winding channel of a standard colonoscope. Based on design requirements for a target procedure, we analyze simulations of two types of continuum robots using recently established kinematic and mechanic modeling approaches: the concentric-tube robot (CTR) and the concentric agonist-antagonist robot (CAAR). In addition, we investigate solutions to the primary engineering challenge to this system, which is accurately transmitting joint motion through exible, hollow shafts. Based on our study of the manipulator simulations and transmission shafts, we select instrument designs for prototyping and testing. We present approaches for controlling the position of the robotic instrument in real-time using an input device, and demonstrate the degree of control we can achieve in various configurations by performing time trial experiments with our prototype robotic instruments. Our observations of the manipulator during testing inform us of sources of error, and we conclude this report with suggestions for future work, including shaft design and alternative continuum manipulator approaches

    Snake-Like Robots for Minimally Invasive, Single Port, and Intraluminal Surgeries

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    The surgical paradigm of Minimally Invasive Surgery (MIS) has been a key driver to the adoption of robotic surgical assistance. Progress in the last three decades has led to a gradual transition from manual laparoscopic surgery with rigid instruments to robot-assisted surgery. In the last decade, the increasing demand for new surgical paradigms to enable access into the anatomy without skin incision (intraluminal surgery) or with a single skin incision (Single Port Access surgery - SPA) has led researchers to investigate snake-like flexible surgical devices. In this chapter, we first present an overview of the background, motivation, and taxonomy of MIS and its newer derivatives. Challenges of MIS and its newer derivatives (SPA and intraluminal surgery) are outlined along with the architectures of new snake-like robots meeting these challenges. We also examine the commercial and research surgical platforms developed over the years, to address the specific functional requirements and constraints imposed by operations in confined spaces. The chapter concludes with an evaluation of open problems in surgical robotics for intraluminal and SPA, and a look at future trends in surgical robot design that could potentially address these unmet needs.Comment: 41 pages, 18 figures. Preprint of article published in the Encyclopedia of Medical Robotics 2018, World Scientific Publishing Company www.worldscientific.com/doi/abs/10.1142/9789813232266_000

    A continuum robotic platform for endoscopic non-contact laser surgery: design, control, and preclinical evaluation

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    The application of laser technologies in surgical interventions has been accepted in the clinical domain due to their atraumatic properties. In addition to manual application of fibre-guided lasers with tissue contact, non-contact transoral laser microsurgery (TLM) of laryngeal tumours has been prevailed in ENT surgery. However, TLM requires many years of surgical training for tumour resection in order to preserve the function of adjacent organs and thus preserve the patient’s quality of life. The positioning of the microscopic laser applicator outside the patient can also impede a direct line-of-sight to the target area due to anatomical variability and limit the working space. Further clinical challenges include positioning the laser focus on the tissue surface, imaging, planning and performing laser ablation, and motion of the target area during surgery. This dissertation aims to address the limitations of TLM through robotic approaches and intraoperative assistance. Although a trend towards minimally invasive surgery is apparent, no highly integrated platform for endoscopic delivery of focused laser radiation is available to date. Likewise, there are no known devices that incorporate scene information from endoscopic imaging into ablation planning and execution. For focusing of the laser beam close to the target tissue, this work first presents miniaturised focusing optics that can be integrated into endoscopic systems. Experimental trials characterise the optical properties and the ablation performance. A robotic platform is realised for manipulation of the focusing optics. This is based on a variable-length continuum manipulator. The latter enables movements of the endoscopic end effector in five degrees of freedom with a mechatronic actuation unit. The kinematic modelling and control of the robot are integrated into a modular framework that is evaluated experimentally. The manipulation of focused laser radiation also requires precise adjustment of the focal position on the tissue. For this purpose, visual, haptic and visual-haptic assistance functions are presented. These support the operator during teleoperation to set an optimal working distance. Advantages of visual-haptic assistance are demonstrated in a user study. The system performance and usability of the overall robotic system are assessed in an additional user study. Analogous to a clinical scenario, the subjects follow predefined target patterns with a laser spot. The mean positioning accuracy of the spot is 0.5 mm. Finally, methods of image-guided robot control are introduced to automate laser ablation. Experiments confirm a positive effect of proposed automation concepts on non-contact laser surgery.Die Anwendung von Lasertechnologien in chirurgischen Interventionen hat sich aufgrund der atraumatischen Eigenschaften in der Klinik etabliert. Neben manueller Applikation von fasergeführten Lasern mit Gewebekontakt hat sich die kontaktfreie transorale Lasermikrochirurgie (TLM) von Tumoren des Larynx in der HNO-Chirurgie durchgesetzt. Die TLM erfordert zur Tumorresektion jedoch ein langjähriges chirurgisches Training, um die Funktion der angrenzenden Organe zu sichern und damit die Lebensqualität der Patienten zu erhalten. Die Positionierung des mikroskopis chen Laserapplikators außerhalb des Patienten kann zudem die direkte Sicht auf das Zielgebiet durch anatomische Variabilität erschweren und den Arbeitsraum einschränken. Weitere klinische Herausforderungen betreffen die Positionierung des Laserfokus auf der Gewebeoberfläche, die Bildgebung, die Planung und Ausführung der Laserablation sowie intraoperative Bewegungen des Zielgebietes. Die vorliegende Dissertation zielt darauf ab, die Limitierungen der TLM durch robotische Ansätze und intraoperative Assistenz zu adressieren. Obwohl ein Trend zur minimal invasiven Chirurgie besteht, sind bislang keine hochintegrierten Plattformen für die endoskopische Applikation fokussierter Laserstrahlung verfügbar. Ebenfalls sind keine Systeme bekannt, die Szeneninformationen aus der endoskopischen Bildgebung in die Ablationsplanung und -ausführung einbeziehen. Für eine situsnahe Fokussierung des Laserstrahls wird in dieser Arbeit zunächst eine miniaturisierte Fokussieroptik zur Integration in endoskopische Systeme vorgestellt. Experimentelle Versuche charakterisieren die optischen Eigenschaften und das Ablationsverhalten. Zur Manipulation der Fokussieroptik wird eine robotische Plattform realisiert. Diese basiert auf einem längenveränderlichen Kontinuumsmanipulator. Letzterer ermöglicht in Kombination mit einer mechatronischen Aktuierungseinheit Bewegungen des Endoskopkopfes in fünf Freiheitsgraden. Die kinematische Modellierung und Regelung des Systems werden in ein modulares Framework eingebunden und evaluiert. Die Manipulation fokussierter Laserstrahlung erfordert zudem eine präzise Anpassung der Fokuslage auf das Gewebe. Dafür werden visuelle, haptische und visuell haptische Assistenzfunktionen eingeführt. Diese unterstützen den Anwender bei Teleoperation zur Einstellung eines optimalen Arbeitsabstandes. In einer Anwenderstudie werden Vorteile der visuell-haptischen Assistenz nachgewiesen. Die Systemperformanz und Gebrauchstauglichkeit des robotischen Gesamtsystems werden in einer weiteren Anwenderstudie untersucht. Analog zu einem klinischen Einsatz verfolgen die Probanden mit einem Laserspot vorgegebene Sollpfade. Die mittlere Positioniergenauigkeit des Spots beträgt dabei 0,5 mm. Zur Automatisierung der Ablation werden abschließend Methoden der bildgestützten Regelung vorgestellt. Experimente bestätigen einen positiven Effekt der Automationskonzepte für die kontaktfreie Laserchirurgie

    Modeling, Analysis, Force Sensing and Control of Continuum Robots for Minimally Invasive Surgery

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    This dissertation describes design, modeling and application of continuum robotics for surgical applications, specifically parallel continuum robots (PCRs) and concentric tube manipulators (CTMs). The introduction of robotics into surgical applications has allowed for a greater degree of precision, less invasive access to more remote surgical sites, and user-intuitive interfaces with enhanced vision systems. The most recent developments have been in the space of continuum robots, whose exible structure create an inherent safety factor when in contact with fragile tissues. The design challenges that exist involve balancing size and strength of the manipulators, controlling the manipulators over long transmission pathways, and incorporating force sensing and feedback from the manipulators to the user. Contributions presented in this work include: (1) prototyping, design, force sensing, and force control investigations of PCRs, and (2) prototyping of a concentric tube manipulator for use in a standard colonoscope. A general kinetostatic model is presented for PCRs along with identification of multiple physical constraints encountered in design and construction. Design considerations and manipulator capabilities are examined in the form of matrix metrics and ellipsoid representations. Finally, force sensing and control are explored and experimental results are provided showing the accuracy of force estimates based on actuation force measurements and control capabilities. An overview of the design requirements, manipulator construction, analysis and experimental results are provided for a CTM used as a tool manipulator in a traditional colonoscope. Currently, tools used in colonoscopic procedures are straight and exit the front of the scope with 1 DOF of operation (jaws of a grasper, tightening of a loop, etc.). This research shows that with a CTM deployed, the dexterity of these tools can be increased dramatically, increasing accuracy of tool operation, ease of use and safety of the overall procedure. The prototype investigated in this work allows for multiple tools to be used during a single procedure. Experimental results show the feasibility and advantages of the newly-designed manipulators

    Designing a robotic port system for laparo-endoscopic single-site surgery

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    Current research and development in the field of surgical interventions aim to reduce the invasiveness by using few incisions or natural orifices in the body to access the surgical site. Considering surgeries in the abdominal cavity, the Laparo-Endoscopic Single-site Surgery (LESS) can be performed through a single incision in the navel, reducing blood loss, post-operative trauma, and improving the cosmetic outcome. However, LESS results in less intuitive instrument control, impaired ergonomic, loss of depth and haptic perception, and restriction of instrument positioning by a single incision. Robot-assisted surgery addresses these shortcomings, by introducing highly articulated, flexible robotic instruments, ergonomic control consoles with 3D visualization, and intuitive instrument control algorithms. The flexible robotic instruments are usually introduced into the abdomen via a rigid straight port, such that the positioning of the tools and therefore the accessibility of anatomical structures is still constrained by the incision location. To address this limitation, articulated ports for LESS are proposed by recent research works. However, they focus on only a few aspects, which are relevant to the surgery, such that a design considering all requirements for LESS has not been proposed yet. This partially originates in the lack of anatomical data of specific applications. Further, no general design guidelines exist and only a few evaluation metrics are proposed. To target these challenges, this thesis focuses on the design of an articulated robotic port for LESS partial nephrectomy. A novel approach is introduced, acquiring the available abdominal workspace, integrated into the surgical workflow. Based on several generated patient datasets and developed metrics, design parameter optimization is conducted. Analyzing the surgical procedure, a comprehensive requirement list is established and applied to design a robotic system, proposing a tendon-driven continuum robot as the articulated port structure. Especially, the aspects of stiffening and sterile design are addressed. In various experimental evaluations, the reachability, the stiffness, and the overall design are evaluated. The findings identify layer jamming as the superior stiffening method. Further, the articulated port is proven to enhance the accessibility of anatomical structures and offer a patient and incision location independent design

    Snake Robots for Surgical Applications: A Review

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    Although substantial advancements have been achieved in robot-assisted surgery, the blueprint to existing snake robotics predominantly focuses on the preliminary structural design, control, and human–robot interfaces, with features which have not been particularly explored in the literature. This paper aims to conduct a review of planning and operation concepts of hyper-redundant serpentine robots for surgical use, as well as any future challenges and solutions for better manipulation. Current researchers in the field of the manufacture and navigation of snake robots have faced issues, such as a low dexterity of the end-effectors around delicate organs, state estimation and the lack of depth perception on two-dimensional screens. A wide range of robots have been analysed, such as the i2Snake robot, inspiring the use of force and position feedback, visual servoing and augmented reality (AR). We present the types of actuation methods, robot kinematics, dynamics, sensing, and prospects of AR integration in snake robots, whilst addressing their shortcomings to facilitate the surgeon’s task. For a smoother gait control, validation and optimization algorithms such as deep learning databases are examined to mitigate redundancy in module linkage backlash and accidental self-collision. In essence, we aim to provide an outlook on robot configurations during motion by enhancing their material compositions within anatomical biocompatibility standards

    Integrating Optimization and Sampling for Robot Motion Planning with Applications in Healthcare

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    Robots deployed in human-centric environments, such as a person's home in a home-assistance setting or inside a person's body in a surgical setting, have the potential to have a large, positive impact on human quality of life. However, for robots to operate in such environments they must be able to move efficiently while avoiding colliding with obstacles such as objects in the person's home or sensitive anatomical structures in the person's body. Robot motion planning aims to compute safe and efficient motions for robots that avoid obstacles, but home assistance and surgical robots come with unique challenges that can make this difficult. For instance, many state of the art surgical robots have computationally expensive kinematic models, i.e., it can be computationally expensive to predict their shape as they move. Some of these robots have hybrid dynamics, i.e., they consist of multiple stages that behave differently. Additionally, it can be difficult to plan motions for robots while leveraging real-world sensor data, such as point clouds. In this dissertation, we demonstrate and empirically evaluate methods for overcoming these challenges to compute high-quality and safe motions for robots in home-assistance and surgical settings. First, we present a motion planning method for a continuum, parallel surgical manipulator that accounts for its computationally expensive kinematics. We then leverage this motion planner to optimize its kinematic design chosen prior to a surgical procedure. Next, we present a motion planning method for a 3-stage lung tumor biopsy robot that accounts for its hybrid dynamics and evaluate the robot and planner in simulation and in inflated porcine lung tissue. Next, we present a motion planning method for a home-assistance robot that leverages real-world, point-cloud obstacle representations. We then expand this method to work with a type of continuum surgical manipulator, a concentric tube robot, with point-cloud anatomical representations. Finally, we present a data-driven machine learning method for more accurately estimating the shape of concentric tube robots. By effectively addressing challenges associated with home assistance and surgical robots operating in human-centric environments, we take steps toward enabling robots to have a positive impact on human quality of life.Doctor of Philosoph

    Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation.

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    Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments

    Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

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    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
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