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Continuum robots offer the dexterity and obstacle circumvention capabilities necessary to enable surgery in deep surgical sites. They also can enable joint-level ex situ force sensing (JEFS), which provides an estimate of end-effector wrenches given joint-level forces. Prior works on JEFS relied on a restrictive embodiment with minimal actuation line friction and captured model and frictional actuation transmission uncertainties using a configuration space formulation. In this work, we overcome these limitations. First, frictional losses are canceled using a feed-forward term based on support vector regression in joint space. Then, regression maps and their interpolation are used to account for actuation hysteresis. The residual joint-force error is then further minimized using a least-squares model parameter update. An indirect hybrid force/position controller using JEFS is presented with evaluation carried out on a realistic pre-clinically deployable insertable robotic effectors platform (IREP) for single-port access surgery. Automated mock force-controlled ablation, exploration, and knot tightening are evaluated. A user study involving the daVinci Research Kit surgeon console and the IREP as a surgical slave was carried out to compare the performance of users with and without force feedback based on JEFS for force-controlled ablation and knot tightening. Results in automated experiments and a user study of telemanipulated experiments suggest that intrinsic force-sensing can achieve levels of force uncertainty and force regulation errors of the order of 0.2 N. Using JEFS and automated task execution, repeatability, and force regulation accuracy is shown to be comparable to using a commercial force sensor for human-in-the-loop feedback. [ABSTRACT FROM AUTHOR]

The navigation of magnetic medical robots typically relies on localizing an actuated, intracorporeal, ferromagnetic body and back-computing a necessary field and gradient that would result in a desired wrench on the device. Uncertainty in this localization degrades the precision of force transmission. Reducing applied force uncertainty may enhance tasks such as in vivo navigation of miniature robots, actuation of magnetically guided catheters, tissue palpation, as well as simply ensuring a bound on forces applied on sensitive tissue. In this paper, we analyze the effects of localization noise on force uncertainty by using sensitivity ellipsoids of the magnetic force Jacobian and introduce an algorithm for uncertainty reduction. We validate the algorithm in both a simulation study and in a physical experiment. In simulation, we observe reductions in estimated force uncertainty by factors of up to 2.8 and 3.1 when using one and two actuating magnets, respectively. On a physical platform, we demonstrate a force uncertainty reduction by a factor of up to 2.5 as measured using an external sensor. Being the first consideration of force uncertainty resulting from noisy localization, this paper provides a strategy for investigators to minimize uncertainty in magnetic force transmission. [ABSTRACT FROM AUTHOR]

Laparoscopic and Single Port Access Surgery (SPAS) present unique dexterity challenges related to dual-arm operations in confined spaces and tele-manipulation of highly dexterous surgical slaves. In an effort to reduce tele-manipulation burden, new paradigms for semi-automating surgical tasks are needed. This paper presents a new minimal constraint suturing and automated choice of handedness for anthropomorphic dual-arm robots. The automated choice of handedness supports surgeons during tele-manipulation of complex robotic slaves where dexterity and workspace constraints are difficult to learn. This criterion is also used to support automated dual-arm rendezvous for quicker suture exchange during dual-arm suturing. The minimal constraint algorithm presented in this paper allows surgeons to operate within a shared-control tele-manipulation framework whereby the surgeon controls the needle insertion speed and the robot controls the needle orientation while respecting a minimalistic set of tissue constraints. This framework is evaluated on a novel insertable robotic end-effectors platform for SPAS. A simulation study demonstrates the effectiveness of the automated choice of handedness criterion through a study of dexterity limitations of each arm. Additional simulations show the proposed algorithm for automated rendezvous and suture exchange. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]