Robotic System Development for Precision MRI-Guided Needle-Based Interventions

This dissertation describes the development of a methodology for implementing robotic systems for interventional procedures under intraoperative Magnetic Resonance Imaging (MRI) guidance. MRI is an ideal imaging modality for surgical guidance of diagnostic and therapeutic procedures, thanks to its ability to perform high resolution, real-time, and high soft tissue contrast imaging without ionizing radiation. However, the strong magnetic field and sensitivity to radio frequency signals, as well as tightly confined scanner bore render great challenges to developing robotic systems within MRI environment. Discussed are potential solutions to address engineering topics related to development of MRI-compatible electro-mechanical systems and modeling of steerable needle interventions. A robotic framework is developed based on a modular design approach, supporting varying MRI-guided interventional procedures, with stereotactic neurosurgery and prostate cancer therapy as two driving exemplary applications. A piezoelectrically actuated electro-mechanical system is designed to provide precise needle placement in the bore of the scanner under interactive MRI-guidance, while overcoming the challenges inherent to MRI-guided procedures. This work presents the development of the robotic system in the aspects of requirements definition, clinical work flow development, mechanism optimization, control system design and experimental evaluation. A steerable needle is beneficial for interventional procedures with its capability to produce curved path, avoiding anatomical obstacles or compensating for needle placement errors. Two kinds of steerable needles are discussed, i.e. asymmetric-tip needle and concentric-tube cannula. A novel Gaussian-based ContinUous Rotation and Variable-curvature (CURV) model is proposed to steer asymmetric-tip needle, which enables variable curvature of the needle trajectory with independent control of needle rotation and insertion. While concentric-tube cannula is suitable for clinical applications where a curved trajectory is needed without relying on tissue interaction force. This dissertation addresses fundamental challenges in developing and deploying MRI-compatible robotic systems, and enables the technologies for MRI-guided needle-based interventions. This study applied and evaluated these techniques to a system for prostate biopsy that is currently in clinical trials, developed a neurosurgery robot prototype for interstitial thermal therapy of brain cancer under MRI guidance, and demonstrated needle steering using both asymmetric tip and pre-bent concentric-tube cannula approaches on a testbed

Semiautonomous Robotic Manipulator for Minimally Invasive Aortic Valve Replacement

Aortic valve surgery is the preferred procedure for replacing a damaged valve with an artificial one. The ValveTech robotic platform comprises a flexible articulated manipulator and surgical interface supporting the effective delivery of an artificial valve by teleoperation and endoscopic vision. This article presents our recent work on force-perceptive, safe, semiautonomous navigation of the ValveTech platform prior to valve implantation. First, we present a force observer that transfers forces from the manipulator body and tip to a haptic interface. Second, we demonstrate how hybrid forward/inverse mechanics, together with endoscopic visual servoing, lead to autonomous valve positioning. Benchtop experiments and an artificial phantom quantify the performance of the developed robot controller and navigator. Valves can be autonomously delivered with a 2.0±0.5 mm position error and a minimal misalignment of 3.4±0.9°. The hybrid force/shape observer (FSO) algorithm was able to predict distributed external forces on the articulated manipulator body with an average error of 0.09 N. FSO can also estimate loads on the tip with an average accuracy of 3.3%. The presented system can lead to better patient care, delivery outcome, and surgeon comfort during aortic valve surgery, without requiring sensorization of the robot tip, and therefore obviating miniaturization constraints.</p

Design, modeling and implementation of a soft robotic neck for humanoid robots

Mención Internacional en el título de doctorSoft humanoid robotics is an emerging field that combines the flexibility and safety of soft robotics with the form and functionality of humanoid robotics. This thesis explores the potential for collaboration between these two fields with a focus on the development of soft joints for the humanoid robot TEO. The aim is to improve the robot’s adaptability and movement, which are essential for an efficient interaction with its environment. The research described in this thesis involves the development of a simple and easily transportable soft robotic neck for the robot, based on a 2 Degree of Freedom (DOF) Cable Driven Parallel Mechanism (CDPM). For its final integration into TEO, the proposed design is later refined, resulting in an efficiently scaled prototype able to face significant payloads. The nonlinear behaviour of the joints, due mainly to the elastic nature of their soft links, makes their modeling a challenging issue, which is addressed in this thesis from two perspectives: first, the direct and inverse kinematic models of the soft joints are analytically studied, based on CDPM mathematical models; second, a data-driven system identification is performed based on machine learning techniques. Both approaches are deeply studied and compared, both in simulation and experimentally. In addition to the soft neck, this thesis also addresses the design and prototyping of a soft arm capable of handling external loads. The proposed design is also tendon-driven and has a morphology with two main bending configurations, which provides more versatility compared to the soft neck. In summary, this work contributes to the growing field of soft humanoid robotics through the development of soft joints and their application to the humanoid robot TEO, showcasing the potential of soft robotics to improve the adaptability, flexibility, and safety of humanoid robots. The development of these soft joints is a significant achievement and the research presented in this thesis paves the way for further exploration and development in this field.La robótica humanoide blanda es un campo emergente que combina la flexibilidad y seguridad de la robótica blanda con la forma y funcionalidad de la robótica humanoide. Esta tesis explora el potencial de colaboración entre estos dos campos centrándose en el desarrollo de una articulación blanda para el cuello del robot humanoide TEO. El objetivo es mejorar la adaptabilidad y el movimiento del robot, esenciales para una interacción eficaz con su entorno. La investigación descrita en esta tesis consiste en el desarrollo de un prototipo sencillo y fácilmente transportable de cuello blando para el robot, basado en un mecanismo paralelo actuado por cable de 2 grados de libertad. Para su integración final en TEO, el diseño propuesto es posteriormente refinado, resultando en un prototipo eficientemente escalado capaz de manejar cargas significativas. El comportamiemto no lineal de estas articulaciones, debido fundamentalmente a la naturaleza elástica de sus eslabones blandos, hacen de su modelado un gran reto, que en esta tesis se aborda desde dos perspectivas diferentes: primero, los modelos cinemáticos directo e inverso de las articulaciones blandas se estudian analíticamente, basándose en modelos matemáticos de mecanismos paralelos actuados por cable; segundo, se aborda el problema de la identificación del sistema mediante técnicas basadas en machine learning. Ambas propuestas se estudian y comparan en profundidad, tanto en simulación como experimentalmente. Además del cuello blando, esta tesis también aborda el diseño de un brazo robótico blando capaz de manejar cargas externas. El diseño propuesto está igualmente basado en accionamiento por tendones y tiene una morfología con dos configuraciones principales de flexión, lo que proporciona una mayor versatilidad en comparación con el cuello robótico blando. En resumen, este trabajo contribuye al creciente campo de la robótica humanoide blanda mediante el desarrollo de articulaciones blandas y su aplicación al robot humanoide TEO, mostrando el potencial de la robótica blanda para mejorar la adaptabilidad, flexibilidad y seguridad de los robots humanoides. El desarrollo de estas articulaciones es una contribución significativa y la investigación presentada en esta tesis allana el camino hacia nuevos desarrollos y retos en este campo.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidenta: Cecilia Elisabet García Cena.- Secretario: Dorin Sabin Copaci.- Vocal: Martin Fodstad Stole