During exploration through tortuous unstructured passages by continuum robots, methods are required to minimize the force interaction between the environment and the robot along its length. This paper presents and evaluates an algorithm for compliant motion control of continuum robots subjected to multiple unknown contacts with the environment. A mapping of external wrenches to a generalized force in the configuration space of a multisegment continuum robot is presented and related to measured joint-level actuation forces. These measurements are applied as inputs to a low-level compliant motion controller. Friction and modeling uncertainties, presenting an unknown nonlinear deviation from the nominal system model, are corrected via a feed-forward estimate provided by a support vector machine. The controller is evaluated on Ø9 and Ø5 mm multisegment continuum robots. We quantify the minimal interaction forces needed to generate compliant motion and demonstrate the ability of the controller to minimize interaction forces during insertion through tortuous passages.

Minimally Invasive Surgery of the throat is predominantly performed trans-orally. Although trans-oral (TO) access provides a scarless access into the airways, its outcomes are affected by complications, high cost, and long setup time. This paper investigates the clinical motivation for trans-nasal (TN) access to the throat and presents the design and hybrid position/compliant motion control of a rapidly deployable endo-nasal telerobotic system. The system exploits a unique Ø5 mm surgical slave with force sensing capabilities used to enable semi-automating the insertion process. Working channels allow the deployment of surgical tools such as a fiberscope, positioning sensors, grippers, suction tubes, cautery, and laser fibers. The treatment of vocal fold paralysis is chosen as a benchmark application and a feasibility study for collagen injection is conducted. Experiments on a realistic human intubation trainer demonstrated successful and safe TN deployment of the end-effector and the feasibility of robotic-assisted treatment of vocal nerve paralysis. We believe this system constitutes a first step toward low-cost office-based head and neck surgical procedures.

Constrained motion control of robotic end-effectors is essential for safe operation in confined spaces such as the urinary bladder. This paper presents the clinical motivation for the development of new control algorithms for robotic-assisted transurethral bladder resection and surveillance using multisegment continuum robots. The anatomy, workspace, and access constraints for this procedure are identified and used as a guideline for the design of the telesurgical system and its control architecture. Constraints are mapped into the configuration space of the robot rather than in task space simplifying the modeling and the enforcement of virtual fixtures. The redundancy resolution is autonomously modified in order to exploit the remaining degrees of freedom using task priority. These methods are validated on a glass model of urinary bladder.

In this paper, we present the integration and preliminary evaluation of a novel Insertable Robotic Effectors Platform (IREP) for Single Port Access Surgery (SPAS). The unique design of the IREP includes planar parallel mechanisms, continuum snake-like arms, wire-actuated wrists, and passive flexible components. While this design has advantages, it presents challenges in terms of modeling, control, and telemanipulation. The complete master-slave resolved-rates telemanipulation framework of the IREP along with its actuation compensation is presented. Experimental evaluation of the capabilities of this new surgical system include bi-manual exchange of rings, pick-and-place tasks, suture passing and knot tying. Results show that the IREP meets the minimal workspace and dexterity requirements specified for laparoscopic surgery, it allows for dual-arm operations such as tool exchange and knot tying in confined spaces. Although it was possible to tie a surgeon's knot with minimal training, suture passing was difficult due to the limited axial rotation of the distal wrists.

This paper presents a novel filtering technique that uses contact detection data and environmental stiffness estimates to register and localize a robot with respect to an a priori 3D surface model. The algorithm leverages geometric constraints within a Kalman filter framework and relies on two distinct update procedures: 1) an equality constrained step for when the robot is forcefully contacting the environment, and 2) an inequality constrained step for when the robot lies in the free-space of the environment. This filtering procedure registers the robot by incrementally eliminating probabilistically infeasible state space regions until a high likelihood solution emerges. In addition to registration and localization, the algorithm can estimate the deformation of the surface model and can detect false positives with respect to contact estimation. This method is experimentally evaluated with an experiment involving a continuum robot interacting with a bench-top flexible structure. The presented algorithm produces an experimental error in registration (with respect to the end-effector position) of 1.1 mm, which is less than 0.8 percent of the robot length.

In this paper, we present a novel kinematic-based framework for collision detection and estimation of contact location along multisegment continuum robots. Screw theory is used to define a screw motion deviation (SMD) as the distance between the expected and the actual instantaneous screw axis (ISA) of motion. The expected ISA is computed based on the unconstrained kinematics model of the robot, while the actual ISA is computed based on sensory information. Collisions with rigid environments at any point along the robot are detected by monitoring the SMD. Contact locations are estimated by the minimization of the SMD between the ISA that is obtained from a constrained kinematic model of the continuum robot and the one that is obtained from sensor data. The proposed contact detection and localization methods only require the relative motion of each continuum segment with respect to its own base. This strategy allows the straightforward generalization of these algorithms for an n -segment continuum robot. The framework is evaluated via simulations and experimentally on a three-segment multibackbone continuum robot. Results show that the collision-detection algorithm is capable of detecting a single collision at any segment, multiple collisions occurring at multiple segments, and total-arm constraint. It is also shown that the estimation of contact location is possible at any location along the continuum robot with an accuracy better than 20% of the segment nominal length. We believe this study will enhance manipulation safety in unstructured environments and confined spaces.

Multi-segment continuum robots offer enhanced safety during surgery due to their inherent passive compliance. However, they suffer poor position tracking performance due to flexibility of their actuation lines, structural compliance, and actuation coupling effects between segments. The need for control methods addressing accurate tracking for multi segment continuum robots is magnified by increased precision requirements of surgical procedures employing these structures. To address this need, this paper proposes a tiered controller that uses both extrinsic and intrinsic sensory information for improved performance of multi-segment continuum robots. The higher tier of this controller uses configuration space feedback while the lower tier uses joint space feedback and a feed-forward term obtained with actuation compensation techniques. We prove the stability of this controller using Lyapunov's direct method and experimentally evaluate its performance on a three-segment multi-backbone continuum robot. Results demonstrate its efficacy in enhancing regulation and tracking performance. It is shown that the controller mitigates the effects of actuation coupling between robot's sub-segments and decreases phase lag. These results suggest that this tiered controller will enhance telemanipulation performance of multi-segment continuum robots.

Novel minimally invasive surgical paradigms accessing deep surgical sites present a new challenge of safe instrument insertion and navigation. This paper addresses this challenge by presenting a new framework for compliant motion control of multi-backbone continuum robots subject to whole-arm contacts. This control framework does not rely on knowledge of contact locations along the length of a continuum robot. Instead, the forces at joint level are applied as controller inputs to generate compliant motion. The paper first presents a new mapping of the external wrenches to a generalized force in the configuration space of a single-stage multi-backbone continuum robot. A closed-form analytic expression for the passive stiffness of a multi-backbone continuum robot segment is also presented. A controller, robust to uncertainties of the system model, is proposed to provide compliant motion of the continuum robot segment by using the generalized force and stiffness definitions. Stability, convergence, and controller properties are shown through experimental validation. The presented framework defines a method for providing compliant motion to continuum robots without explicit knowledge of the environment. We believe this work enables new control algorithms for rapidly deployable surgical robots and supports novel surgical paradigms by increasing safety during unstructured interaction with flexible anatomy.

Continuum robots offer significant advantages for surgical intervention due to their down-scalability, dexterity, and structural flexibility. While structural compliance offers a passive way to guard against trauma, it necessitates robust methods for online estimation of the robot configuration in order to enable precise position and manipulation control. In this paper, we address the pose estimation problem by applying a novel mapping of the robot configuration to a feature descriptor space using stereo vision. We generate a mapping of known features through a supervised learning algorithm that relates the feature descriptor to known ground truth. Features are represented in a reduced sub-space, which we call eigen-features. The descriptor provides some robustness to occlusions, which are inherent to surgical environments, and the methodology that we describe can be applied to multi-segment continuum robots for closed-loop control. Experimental validation on a single-segment continuum robot demonstrates the robustness and efficacy of the algorithm for configuration estimation. Results show that the errors are in the range of 1°.

This paper presents a novel modeling framework for contact detection and estimation of contact location on multi-backbone continuum robots. The paper presents modified kinematics for constrained continuum robots and introduces the concept of Fixed Centrode Deviation (FCD) for continuum robots. It is shown that the change in fixed centrode locus may be used for detection of contact and for contact location estimation. An alternative method for contact detection using Joint Force Deviation (JFD) is investigated and a lower bound for contact detectability is derived while considering uncertainties in joint forces. An estimation framework for the location of contact is presented based on FCD and the constrained kinematics Jacobian of the continuum robot. These methods are validated by simulation and experiments. This framework may be used for enhancing the safety of robotic surgical slaves and for exploration of unknown environments such as in scenarios of search and rescue.