Closed-loop control of soft continuum manipulators under tip follower actuation.

Continuum manipulators, inspired by nature, have drawn significant interest within the robotics community. They can facilitate motion within complex environments where traditional rigid robots may be ineffective, while maintaining a reasonable degree of precision. Soft continuum manipulators have emerged as a growing subfield of continuum robotics, with promise for applications requiring high compliance, including certain medical procedures. This has driven demand for new control schemes designed to precisely control these highly flexible manipulators, whose kinematics may be sensitive to external loads, such as gravity. This article presents one such approach, utilizing a rapidly computed kinematic model based on Cosserat rod theory, coupled with sensor feedback to facilitate closed-loop control, for a soft continuum manipulator under tip follower actuation and external loading. This approach is suited to soft manipulators undergoing quasi-static deployment, where actuators apply a follower wrench (i.e., one that is in a constant body frame direction regardless of robot configuration) anywhere along the continuum structure, as can be done in water-jet propulsion. In this article we apply the framework specifically to a tip actuated soft continuum manipulator. The proposed control scheme employs both actuator feedback and pose feedback. The actuator feedback is utilized to both regulate the follower load and to compensate for non-linearities of the actuation system that can introduce kinematic model error. Pose feedback is required to maintain accurate path following. Experimental results demonstrate successful path following with the closed-loop control scheme, with significant performance improvements gained through the use of sensor feedback when compared with the open-loop case.

Accuracy of Touch-Based Registration During Robotic Image-Guided Partial Nephrectomy Before and After Tumor Resection in Validated Phantoms.

Aim: Image-guided surgery (IGS) allows for accurate, real-time localization of subsurface critical structures during surgery. No prior IGS systems have described a feasible method of intraoperative reregistration after manipulation of the kidney during robotic partial nephrectomy (PN). We present a method for seamless reregistration during IGS and evaluate accuracy before and after tumor resection in two validated kidney phantoms. Materials and Methods: We performed robotic PN on two validated kidney phantoms-one with an endophytic tumor and one with an exophytic tumor-with our IGS system utilizing the da Vinci Xi robot. Intraoperatively, the kidney phantoms' surfaces were digitized with the da Vinci robotic manipulator via a touch-based method and registered to a three-dimensional segmented model created from cross-sectional CT imaging of the phantoms. Fiducial points were marked with a surgical marking pen and identified after the initial registration using the robotic manipulator. Segmented images were displayed via picture-in-picture in the surgeon console as tumor resection was performed. After resection, reregistration was performed by reidentifying the fiducial points. The accuracy of the initial registration and reregistration was compared. Results: The root mean square (RMS) averages of target registration error (TRE) were 2.53 and 4.88 mm for the endophytic and exophytic phantoms, respectively. IGS enabled resection along preplanned contours. Specifically, the RMS averages of the normal TRE over the entire resection surface were 0.75 and 2.15 mm for the endophytic and exophytic phantoms, respectively. Both tumors were resected with grossly negative margins. Point-based reregistration enabled instantaneous reregistration with minimal impact on RMS TRE compared with the initial registration (from 1.34 to 1.70 mm preresection and from 1.60 to 2.10 mm postresection). Conclusions: We present a novel and accurate registration and reregistration framework for use during IGS for PN with the da Vinci Xi surgical system. The technology is easily integrated into the surgical workflow and does not require additional hardware.

Online Disturbance Estimation for Improving Kinematic Accuracy in Continuum Manipulators.

Continuum manipulators are flexible robots which undergo continuous deformation as they are actuated. To describe the elastic deformation of such robots, kinematic models have been developed and successfully applied to a large variety of designs and to various levels of constitutive stiffness. Independent of the design, kinematic models need to be calibrated to best describe the deformation of the manipulator. However, even after calibration, unmodeled effects such as friction, nonlinear elastic and/or spatially varying material properties as well as manufacturing imprecision reduce the accuracy of these models. In this paper, we present a method for improving the accuracy of kinematic models of continuum manipulators through the incorporation of orientation sensor feedback. We achieve this through the use of a "disturbance wrench", which is used to compensate for these unmodeled effects, and is continuously estimated based on orientation sensor feedback as the robot moves through its workspace. The presented method is applied to the HydroJet, a waterjet-actuated soft continuum manipulator, and shows an average of 40% reduction in root mean square position and orientation error in the two most common types of kinematic models for continuum manipulators, a Cosserat rod model and a pseudo-rigid body model.

Toward Practical and Accurate Touch-Based Image Guidance for Robotic Partial Nephrectomy.

Partial nephrectomy involves removing a tumor while sparing surrounding healthy kidney tissue. Compared to total kidney removal, partial nephrectomy improves outcomes for patients but is underutilized because it is challenging to accomplish minimally invasively, requiring accurate spatial awareness of unseen subsurface anatomy. Image guidance can enhance spatial awareness by displaying a 3D model of anatomical relationships derived from medical imaging information. It has been qualitatively suggested that the da Vinci robot is well suited to facilitate image guidance through touch-based registration. In this paper we validate and advance this concept toward real-world use in several important ways. First, we contribute the first quantitative accuracy evaluation of touch-based registration with the da Vinci. Next, we demonstrate real-time touch-based registration and display of medical images for the first time. Lastly, we perform the first experiments validating use of touch-based image guidance to improve a surgeon's ability to localize subsurface anatomical features in a geometrically realistic phantom.

Toward Transoral Peripheral Lung Access: Combining Continuum Robots and Steerable Needles.

Lung cancer is the most deadly form of cancer in part because of the challenges associated with accessing nodules for diagnosis and therapy. Transoral access is preferred to percutaneous access since it has a lower risk of lung collapse, yet many sites are currently unreachable transorally due to limitations with current bronchoscopic instruments. Toward this end, we present a new robotic system for image-guided trans-bronchoscopic lung access. The system uses a bronchoscope to navigate in the airway and bronchial tubes to a site near the desired target, a concentric tube robot to move through the bronchial wall and aim at the target, and a bevel-tip steerable needle with magnetic tracking to maneuver through lung tissue to the target under closed-loop control. In this work, we illustrate the workflow of our system and show accurate targeting in phantom experiments. Ex vivo porcine lung experiments show that our steerable needle can be tuned to achieve appreciable curvature in lung tissue. Lastly, we present targeting results with our system using two scenarios based on patient cases. In these experiments, phantoms were created from patient-specific computed tomography information and our system was used to target the locations of suspicious nodules, illustrating the ability of our system to reach sites that are traditionally inaccessible transorally.

Tendons, Concentric Tubes, and a Bevel Tip: Three Steerable Robots in One Transoral Lung Access System.

Lung cancer is the most deadly form of cancer, and survival depends on early-stage diagnosis and treatment. Transoral access is preferable to traditional between-the-ribs needle insertion because it is less invasive and reduces risk of lung collapse. Yet many sites in the peripheral zones of the lung or distant from the bronchi cannot currently be accessed transorally, due to the relatively large diameter and lack of sufficient steerablity of current instrumentation. To remedy this, we propose a new robotic system that uses a tendon-actuated device (bronchoscope) as a first stage for deploying a concentric tube robot, which itself is a vehicle through which a bevel steered needle can be introduced into the soft tissue of the lung outside the bronchi. In this paper we present the various components of the system and the workflow we envision for deploying the robot to a target using image guidance. We describe initial validation experiments in which we puncture ex vivo bronchial wall tissue and also target a nodule in a phantom with an average final tip error of 0.72 mm.

A robot for transnasal surgery featuring needle-sized tentacle-like arms.

This paper discusses a new class of robots known as concentric tube robots and their application to transnasal skull base surgery. The endonasal approach has clear benefits for patients, but the surgery presents challenges that strongly motivate the use of robotic tools. In this paper, the concentric tube robot concept is described, and preliminary experimental results for transnasal skull base surgery are reviewed. Just as the da Vinci robot has revolutionized many laparoscopic surgeries, we expect concentric tube robots will enable the advancement of skull base surgery and the development of other minimally invasive procedures that require access through constrained paths.