Christopher R. Carlson

Mechanics Modeling of Tendon-Driven Continuum Manipulators

Continuum robotic manipulators articulate due to their inherent compliance. Tendon actuation leads to compression of the manipulator, extension of the actuators, and is limited by the practical constraint that tendons cannot support compression. In light of these observations, we present a new linear model for transforming desired beam configuration to tendon displacements and vice versa. We begin from first principles in solid mechanics by analyzing the effects of geometrically nonlinear tendon loads. These loads act both distally at the termination point and proximally along the conduit contact interface. The resulting model simplifies to a linear system including only the bending and axial modes of the manipulator as well as the actuator compliance. The model is then manipulated to form a concise mapping from beam configuration-space parameters to n redundant tendon displacements via the internal loads and strains experienced by the system. We demonstrate the utility of this model by implementing an optimal feasible controller. The controller regulates axial strain to a constant value while guaranteeing positive tendon forces and minimizing their magnitudes over a range of articulations. The mechanics-based model from this study provides insight as well as performance gains for this increasingly ubiquitous class of manipulators.

Flexible Robotic Retrograde Renoscopy: Description of Novel Robotic Device and Preliminary Laboratory Experience

OBJECTIVES To describe a novel flexible robotic system for performing retrograde intrarenal surgery. METHODS Remote robotic flexible ureterorenoscopy was performed bilaterally in 5 acute swine (10 kidneys). A novel 14F robotic catheter system, which manipulated a passive optical fiberscope mounted on a remote catheter manipulator was used. The technical feasibility, efficiency, and reproducibility of accessing all calices were assessed. Additionally, laser lithotripsy of calculi and laser ablation of renal papillae were performed. RESULTS The robotic catheter system could be introduced de novo in eight ureters; two ureters required balloon dilation. The ureteroscope could be successfully manipulated remotely into 83 (98%) of the 85 calices. The time required to inspect all calices within a given kidney decreased with experience from 15 minutes in the first kidney to 49 seconds in the last (mean 4.6 minutes). On a visual analog scale (1, worst to 10, best), the reproducibility of caliceal access was rated at 8, and instrument tip stability was rated at 10. A renal pelvic perforation constituted the solitary complication. Histologic examination of the ureter showed changes consistent with acute dilation without areas of necrosis. CONCLUSIONS A novel robotic catheter system is described for performing retrograde ureterorenoscopy. The potential advantages compared with conventional manual flexible ureterorenoscopy include an increased range of motion, instrument stability, and improved ergonomics. Ongoing refinement is likely to expand the role of this technology in retrograde intrarenal surgery in the near future.

Vision based 3-D shape sensing of flexible manipulators

Rigid robotic manipulators employ traditional sensors such as encoders or potentiometers to measure joint angles and determine end-effector position. Manipulators that are flexible, however, introduce motions that are much more difficult to measure. This is especially true for continuum manipulators that articulate by means of material compliance. In this paper, we present a vision based system for quantifying the 3-D shape of a flexible manipulator in real-time. The sensor system is validated for accuracy with known point measurements and for precision by estimating a known 3-D shape. We present two applications of the validated system relating to the open-loop control of a tendon driven continuum manipulator. In the first application, we present a new continuum manipulator model and use the sensor to quantify 3-D performance. In the second application, we use the shape sensor system for model parameter estimation in the absence of tendon tension information.

An Ultrasound-based Localization Algorithm for Catheter Ablation Guidance in the Left Atrium

We present a method for catheter localization in the left atrium based on the unscented particle filter (UPF), a Monte Carlo method employed in stochastic state estimation. Using an intracardiac echo (ICE) ultrasound catheter, we acquire ultrasound images of the atrium from multiple configurations and iteratively determine the catheter’s pose with respect to anatomy. At each time step, the catheter’s change in pose is determined using either a six-degree-of-freedom electromagnetic pose sensor or a robotic guide catheter whose kinematics serve as a pseudo-pose measurement. Sensor and kinematic model uncertainties are explicitly considered when computing the localization estimate. Acquired ultrasound images are compared with simulated ultrasound images based on segmented computed tomography (CT) or magnetic resonance (MR) data of the left atrium. The results of these comparisons are used to refine the localization estimate. After considering less than 30 seconds’ worth of ICE data, our algorithm converges to an accurate pose estimate. Furthermore, our algorithm is robust to sensor drift and kinematic model errors, as well as gradual, unmodeled movements in the anatomy. Such problems typically complicate traditional image-based localization.

Task-Space Control of Continuum Manipulators with Coupled Tendon Drive

Robotic control of flexible devices can enhance and simplify many medical procedures. We present a method for controlling the distal tip motion of a tendon driven cardiac catheter. The catheter’s shape is specified by a mechanics model which includes coupling of multiple sections. Shape is then transformed to end-effector location using a D-H kinematics model. The combined models are then inverted to translate desired tip motion to tendon displacement. The inversion optimizes positive tendon tension for n-arbitrarily located tendons. To validate the method, we present a bench-top experiment of a cardiac catheter emulating a circular ablation as a 6-DOF task. To reduce error, we present the first known experiments of sensor feedback control on the tip position of a continuum manipulator. The resulting system performs with sub-millimeter accuracy.

An Incremental Method for Registering Electroanatomic Mapping Data to Surface Mesh Models of the Left Atrium

We present a method for registering position and orientation data collected from an electroanatomic mapping system (EMS) to a surface mesh based on segmented Computed Tomography (CT) or Magnetic Resonance (MR) images of the left atrium. Our algorithm is based on the Unscented Particle Filter (UPF) for stochastic state estimation. Using an intracardiac echo (ICE) ultrasound catheter with mounted mapping sensor, we acquire ultrasound images of the atrium from multiple configurations and iteratively determine the catheters pose with respect to anatomy. After considering less than a minutes worth of ICE data, the algorithm converges to an accurate pose estimate which, in turn, yields the registration parameters transforming EMS coordinates to mesh coordinates. The iterative framework of the UPF allows us to be robust to unmodeled EMS noise and drift, problems which complicate traditional registration methods assuming regularity in image data structure.

A probabilistic framework for freehand 3D ultrasound reconstruction applied to catheter ablation guidance in the left atrium

IntroductionThe catheter ablation procedure is a minimally invasive surgery used to treat atrial fibrillation. Difficulty visualizing the catheter inside the left atrium anatomy has led to lengthy procedure times and limited success rates. In this paper, we present a set of algorithms for reconstructing 3D ultrasound data of the left atrium in real-time, with an emphasis on automatic tissue classification for improved clarity surrounding regions of interest.MethodsUsing an intracardiac echo (ICE) ultrasound catheter, we collect 2D-ICE images of a left atrium phantom from multiple configurations and iteratively compound the acquired data into a 3D-ICE volume. We introduce two new methods for compounding overlapping US data—occupancy-likelihood and response-grid compounding—which automatically classify voxels as “occupied” or “clear,” and mitigate reconstruction artifacts caused by signal dropout. Finally, we use the results of an ICE-to-CT registration algorithm to devise a response-likelihood weighting scheme, which assigns weights to US signals based on the likelihood that they correspond to tissue-reflections.ResultsOur algorithms successfully reconstruct a 3D-ICE volume of the left atrium with voxels classified as “occupied” or “clear,” even within difficult-to-image regions like the pulmonary vein openings. We are robust to dropout artifact that plagues a subset of the 2D-ICE images, and our weighting scheme assists in filtering out spurious data attributed to ghost-signals from multi-path reflections. By automatically classifying tissue, our algorithm precludes the need for thresholding, a process that is difficult to automate without subjective input. Our hope is to use this result towards developing 3D ultrasound segmentation algorithms in the future.

Catheter localization in the left atrium using an outdated anatomic reference for guidance

We present a method for registering real-time ultrasound of the left atrium to an outdated, anatomic surface mesh model, whose shape differs from that of the anatomy. Using an intracardiac echo (ICE) catheter with mounted 6DOF electromagnetic position/orientation sensor (EPS), we acquire images of the left atrium and determine where the ICE catheter must be positioned relative to the surface mesh to generate similar, “virtual” ICE images. Further, we use an affine warping model to infer how the shape of the surface mesh differs from that of the atrium. Our registration and warping algorithm allows us to display EPS-sensorized catheters inside the surface mesh, facilitating guidance for left atrial procedures. By solving for the atrium-to-mesh warping parameters, we ensure that tissue contact in the anatomy is properly displayed as tissue contact in the mesh. After considering less than thirty seconds worth of ICE data, we are able to accurately localize EPS measurements within the surface mesh, despite surface mesh warpings of up to ±20% along and about the principal axes of the left atrium. Further, because our estimation framework is iterative and continuous, our accuracy improves as new data is acquired.

An Image-Based Localization Algorithm for Catheter Navigation in the Left Atrium

We present a sensorless method for localizing a robotic catheter inside the left atrium using intracardiac echo (ICE) ultrasound. As the robotic catheter navigates inside the anatomy, its kinematics provide a rough estimate of change in pose. At the same time, an ICE catheter inserted through the robotic catheter’s lumen acquires images to refine this estimate.