Concentric Tube Robot Design and Optimization Based on Task and Anatomical Constraints

Concentric tube robots are catheter-sized continuum robots that are well suited for minimally invasive surgery inside confined body cavities. These robots are constructed from sets of pre-curved superelastic tubes and are capable of assuming complex 3D curves. The family of 3D curves that the robot can assume depends on the number, curvatures, lengths and stiffnesses of the tubes in its tube set. The robot design problem involves solving for a tube set that will produce the family of curves necessary to perform a surgical procedure. At a minimum, these curves must enable the robot to smoothly extend into the body and to manipulate tools over the desired surgical workspace while respecting anatomical constraints. This paper introduces an optimization framework that utilizes procedureor patient-specific image-based anatomical models along with surgical workspace requirements to generate robot tube set designs. The algorithm searches for designs that minimize robot length and curvature and for which all paths required for the procedure consist of stable robot configurations. Two mechanics-based kinematic models are used. Initial designs are sought using a model assuming torsional rigidity. These designs are then refined using a torsionally-compliant model. The approach is illustrated with clinically relevant examples from neurosurgery and intracardiac surgery

Sensorisation of a novel biologically inspired flexible needle

Percutaneous interventions are commonly performed during minimally invasive brain surgery, where a straight rigid instrument is inserted through a small incision to access a deep lesion in the brain. Puncturing a vessel during this procedure can be a life-threatening complication. Embedding a forward-looking sensor in a rigid needle has been proposed to tackle this problem; however, using a rigid needle, the procedure needs to be interrupted if a vessel is detected. Steerable needle technology could be used to avoid obstacles, such as blood vessels, due to its ability to follow curvilinear paths, but research to date was lacking in this respect. This thesis aims to investigate the deployment of forward-looking sensors for vessel detection in a steerable needle. The needle itself is based on a bioinspired programmable bevel-tip needle (PBN), a multi-segment design featuring four hollow working channels. In this thesis, laser Doppler flowmetry (LDF) is initially characterised to ensure that the sensor fulfils the minimum requirements for it to be used in conjunction with the needle. Subsequently, vessel reconstruction algorithms are proposed. To determine the axial and off-axis position of the vessel with respect to the probe, successive measurements of the LDF sensor are used. Ideally, full knowledge of the vessel orientation is required to execute an avoidance strategy. Using two LDF probes and a novel signal processing method described in this thesis, the predicted possible vessel orientations can be reduced to four, a setup which is explored here to demonstrate viable obstacle detection with only partial sensor information. Relative measurements from four LDF sensors are also explored to classify possible vessel orientations in full and without ambiguity, but under the assumption that the vessel is perpendicular to the needle insertion axis. Experimental results on a synthetic grey matter phantom are presented, which confirm these findings. To release the perpendicularity assumption, the thesis concludes with the description of a machine learning technique based on a Long Short-term memory network, which enables a vessel's spatial position, cross-sectional diameter and full pose to be predicted with sub-millimetre accuracy. Simulated and in-vitro examinations of vessel detection with this approach are used to demonstrate effective predictive ability. Collectively, these results demonstrate that the proposed steerable needle sensorisation is viable and could lead to improved safety during robotic assisted needle steering interventions.Open Acces

Modeling, Sensorization and Control of Concentric-Tube Robots

Since the concept of the Concentric-Tube Robot (CTR) was proposed in 2006, CTRs have been a popular research topic in the field of surgical robotics. The unique mechanical design of this robot allows it to navigate through narrow channels in the human anatomy and operate in highly constrained environments. It is therefore likely to become the next generation of surgical robots to overcome the challenges that cannot be addressed by current technologies. In CSTAR, we have had ongoing work over the past several years aimed at developing novel techniques and technologies for CTRs. This thesis describes the contributions made in this context, focusing primarily on topics such as modeling, sensorization, and control of CTRs. Prior to this work, one of the main challenges in CTRs was to develop a kinematic model that achieves a balance between the numerical accuracy and computational efficiency for surgical applications. In this thesis, a fast kinematic model of CTRs is proposed, which can be solved at a comparatively fast rate (0.2 ms) with minimal loss of accuracy (0.1 mm) for a 3-tube CTR. A Jacobian matrix is derived based on this model, leading to the development of a real-time trajectory tracking controller for CTRs. For tissue-robot interactions, a force-rejection controller is proposed for position control of CTRs under time-varying force disturbances. In contrast to rigid-link robots, instability of position control could be caused by non-unique solutions to the forward kinematics of CTRs. This phenomenon is modeled and analyzed, resulting in design criteria that can ensure kinematic stability of a CTR in its entire workspace. Force sensing is another major difficulty for CTRs. To address this issue, commercial force/torque sensors (Nano43, ATI Industrial Automation, United States) are integrated into one of our CTR prototypes. These force/torque sensors are replaced by Fiber-Bragg Grating (FBG) sensors that are helically-wrapped and embedded in CTRs. A strain-force calculation algorithm is proposed, to convert the reflected wavelength of FBGs into force measurements with 0.1 N force resolution at 100 Hz sampling rate. In addition, this thesis reports on our innovations in prototyping drive units for CTRs. Three designs of CTR prototypes are proposed, the latest one being significantly more compact and cost efficient in comparison with most designs in the literature. All of these contributions have brought this technology a few steps closer to being used in operating rooms. Some of the techniques and technologies mentioned above are not merely limited to CTRs, but are also suitable for problems arising in other types of surgical robots, for example, for sensorizing da Vinci surgical instruments for force sensing (see Appendix A)

Modelling, synthesis and model-based motion planning for hyper-redundant, binary actuated manipulators

Die Untersuchung von schwer zu erreichenden Hohlräumen durch schmale Zugänge wird im technischen Umfeld als Boroskopie und in der Medizin als Endoskopie bezeichnet. Wenn neben der reinen Inspektion auch eine Manipulation erfolgen soll, wird ergänzend zu einer guten Anpassbarkeit an gekrümmte Pfade auch eine stabile Arbeitsplattform zur Aufnahme von Manipulationskräften benötigt. Einen Ansatz, die daraus resultierenden Anforderungen an die verwendeten Systeme zu adressieren, stellen schlangenartige Roboter dar. Ihre hyperredundante Struktur aus einzelnen Stellgliedern bietet eine vielseitige Positionierbarkeit. Die Verwendung von binären, kippstabilen Aktoren beschränkt zwar den Arbeitsraum auf wenige diskrete Punkte, bietet aber – in Abhängigkeit vom Antriebsmechanismus – besonders hohe Haltemomente und ermöglicht damit eine gezielte Systemversteifung. Eine Kombination beider Ansätze zur Klasse der binär aktuierten, hyperredundanten Manipulatoren ist in der Lage, diese Anforderungen zu erfüllen, jedoch existiert deutlicher Forschungsbedarf hinsichtlich Methoden zur optimalen Auslegung sowie zur gezielten Verfolgung von Referenzpfaden, sodass Kern der vorliegenden Arbeit die Erforschung der modellbasierten Bewegungsplanung dieser Roboterklasse ist. Voraussetzung für eine hohe Pfadfolgegenauigkeit ist, dass der Manipulator sich grundsätzlich gut an einen vorgegebenen Referenzpfad anschmiegen kann. Der Einschränkungsgrad durch die diskrete Positionierbarkeit des Manipulators ist dabei abhängig von den geometrischen Parametern der einzelnen Segmente. Die Untersuchungen in dieser Arbeit zeigen, dass durch die Analyse kinematischer Leistungsmerkmale, wie Arbeitsraum(-dichte) oder erzielbarer Krümmungsradius, kein allgemeingültiges optimales Design gefunden werden kann. Daher wird eine Maßsynthese unter Berücksichtigung von Randbedingungen entworfen, in der optimale geometrische Parameter eines einzelnen binären Aktors synthetisiert werden. Darauf aufbauend wird eine Pfadverfolgung gemäß dem „Follow-the-Leader“-Prinzip erarbeitet. Grundidee ist, dass das Endeffektorsegment den Referenzpfad exploriert, während alle weiteren Aktoren dem führenden Segment automatisch folgen. Da binäre Aktoren einen nicht-kontinuierlichen Schaltprozess aufweisen, wird ein modellbasierter Ansatz für die Bestimmung optimaler Schaltsequenzen vorgeschlagen, die zu jedem Zeitpunkt eine hohe Pfadtreue garantieren. Die anschließende experimentelle Evaluation erfolgt nach der Modellierung und Identifikation relevanter Parameter für den Prototyp einer elektromagnetischen Kippaktorkette. Grundsätzlich kann die Funktionsfähigkeit der in dieser Arbeit erforschten Methoden zur Bewegungsplanung sowohl in der Simulation als auch experimentell nachgewiesen werden.The investigation of difficult to reach cavities through narrow accesses is called borescopy in the technical environment and endoscopy in medicine. If manipulation is to be performed in addition to pure inspection, a stable working platform is required to withstand manipulation forces in combination with good adaptability to curved paths. One approach to address the resulting requirements for the systems used are snake-like robots. Their hyper-redundant structure of individual actuators allows for versatile positioning. Although the use of binary, tilt-stable actuators limits the working space to a few discrete points, they offer - depending on the drive mechanism - particularly high holding torques and thus enable a targeted system stiffening. A combination of both approaches to the class of binary actuated, hyper-redundant manipulators is able to meet the required requirements, however, there is a clear need for research into methods for optimal design and the targeted pursuit of reference paths, so that the core of the present work consists the investigation of model-based motion planning of this robot class. A prerequisite for a high path following accuracy is that the manipulator is able to adapt well to a given reference path. The degree of limitation due to discrete positionability of the manipulator depends on the geometric parameters of the individual segments. The studies in this thesis show that the analysis of kinematic performance characteristics, such as work space (density) or achievable radius of curvature, does not lead to a generally valid optimal design. Therefore, a dimensional synthesis is developed under consideration of boundary conditions, in which optimal geometric parameters of a single binary actuator are synthesized. Based on this, a path following according to the "Follow-the-Leader"principle is elaborated. The basic idea is that the end effector segment explores the reference path, while all other actuators automatically follow the leading segment. Since binary actuators have a discontinuous switching process, a model-based approach is proposed for determining optimal switching sequences that guarantee high path accuracy at all times. The subsequent experimental evaluation is performed after modelling and identification of relevant parameters for the prototype of an electromagnetic tilting actuator chain. In principle, the functionality of the motion planning methods investigated in this thesis are proven both in simulation and experimentally

Design, Modeling and Control of Micro-scale and Meso-scale Tendon-Driven Surgical Robots

Manual manipulation of passive surgical tools is time consuming with uncertain results in cases of navigating tortuous anatomy, avoiding critical anatomical landmarks, and reaching targets not located in the linear range of these tools. For example, in many cardiovascular procedures, manual navigation of a micro-scale passive guidewire results in increased procedure times and radiation exposure. This thesis introduces the design of two steerable guidewires: 1) A two degree-of-freedom (2-DoF) robotic guidewire with orthogonally oriented joints to access points in a three dimensional workspace, and 2) a micro-scale coaxially aligned steerable (COAST) guidewire robot that demonstrates variable and independently controlled bending length and curvature of the distal end. The 2-DoF guidewire features two micromachined joints from a tube of superelastic nitinol of outer diameter 0.78 mm. Each joint is actuated with two nitinol tendons. The joints that are used in this robot are called bidirectional asymmetric notch (BAN) joints, and the advantages of these joints are explored and analyzed. The design of the COAST robotic guidewire involves three coaxially aligned tubes with a single tendon running centrally through the length of the robot. The outer tubes are made from micromachined nitinol allowing for tendon-driven bending of the robot at variable bending curvatures, while an inner stainless steel tube controls the bending length of the robot. By varying the lengths of the tubes as well as the tendon, and by insertion and retraction of the entire assembly, various joint lengths and curvatures may be achieved. Kinematic and static models, a compact actuation system, and a controller for this robot are presented. The capability of the robot to accurately navigate through phantom anatomical bifurcations and tortuous angles is also demonstrated in three dimensional phantom vasculature. At the meso-scale, manual navigation of passive pediatric neuroendoscopes for endoscopic third ventriculostomy may not reach target locations in the patient's ventricle. This work introduces the design, analysis and control of a meso-scale two degree-of-freedom robotic bipolar electrocautery tool that increases the workspace of the neurosurgeon. A static model is proposed for the robot joints that avoids problems arising from pure kinematic control. Using this model, a control system is developed that comprises of a disturbance observer to provide precise force control and compensate for joint hysteresis. A handheld controller is developed and demonstrated in this thesis. To allow the clinician to estimate the shape of the steerable tools within the anatomy for both micro-scale and meso-scale tools, a miniature tendon force sensor and a high deflection shape sensor are proposed and demonstrated. The force sensor features a compact design consisting of a single LED, dual-phototransistor, and a dual-screen arrangement to increase the linear range of sensor output and compensate for external disturbances, thereby allowing force measurement of up to 21 N with 99.58 % accuracy. The shape sensor uses fiber Bragg grating based optical cable mounted on a micromachined tube and is capable of measuring curvatures as high as 145 /m. These sensors were incorporated and tested in the guidewire and the neuroendoscope tool robots and can provide robust feedback for closed-loop control of these devices in the future.Ph.D