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. 2021 Feb;26(1):369-380.
doi: 10.1109/tmech.2020.3020504. Epub 2020 Aug 31.

A Surgical Robotic System for Treatment of Pelvic Osteolysis Using an FBG-Equipped Continuum Manipulator and Flexible Instruments

Shahriar Sefati  1 , Rachel Hegeman  2 , Farshid Alambeigi  3 , Iulian Iordachita  1 , Peter Kazanzides  1 , Harpal Khanuja  4 , Russell H Taylor  1 , Mehran Armand  5
Affiliations

A Surgical Robotic System for Treatment of Pelvic Osteolysis Using an FBG-Equipped Continuum Manipulator and Flexible Instruments

Shahriar Sefati et al. IEEE ASME Trans Mechatron. 2021 Feb.

Abstract

This paper presents the development and experimental evaluation of a redundant robotic system for the less-invasive treatment of osteolysis (bone degradation) behind the acetabular implant during total hip replacement revision surgery. The system comprises a rigid-link positioning robot and a Continuum Dexterous Manipulator (CDM) equipped with highly flexible debriding tools and a Fiber Bragg Grating (FBG)-based sensor. The robot and the continuum manipulator are controlled concurrently via an optimization-based framework using the Tip Position Estimation (TPE) from the FBG sensor as feedback. Performance of the system is evaluated on a setup that consists of an acetabular cup and saw-bone phantom simulating the bone behind the cup. Experiments consist of performing the surgical procedure on the simulated phantom setup. CDM TPE using FBGs, target location placement, cutting performance, and the concurrent control algorithm capability in achieving the desired tasks are evaluated. Mean and standard deviation of the CDM TPE from the FBG sensor and the robotic system are 0.50 mm, and 0.18 mm, respectively. Using the developed surgical system, accurate positioning and successful cutting of desired straight-line and curvilinear paths on saw-bone phantoms behind the cup with different densities are demonstrated. Compared to the conventional rigid tools, the workspace reach behind the acetabular cup is 2.47 times greater when using the developed robotic system.

Keywords: Continuum Manipulator; Fiber Bragg Grating; Minimally-Invasive Surgery; Orthopedic Surgery.

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Figures

Fig. 1.
Fig. 1.
Robot-assisted treatment of Osteolysis. The continuum manipulator developed for orthopaedic applications equipped with flexible instruments inserted through a screw hole of the acetabular implant.
Fig. 2.
Fig. 2.
(a) Redundant surgical system and the custom-designed optical tracker reference geometry used for hand-eye calibration and training the data-driven algorithm for FBG sensing, (b) system during cutting of saw-bone phantom behind the acetabular cup component using flexible debriding tools.
Fig. 3.
Fig. 3.
(a) Tool actuation unit comprised of a DC motor and transmission belt with collet clamping mechanism that holds the tool shaft, (b) the CDM actuation unit comprised of the three DC motors, one for axial roll motion and two for CDM actuation, with the two CDM cable DOFs and the axial roll DOF demonstrated in solid orange arrows, (c) flexible cutting/debriding tool comprised of a flexible torque coil and ball-end mill, (d) tool integration into the CDM, and (e) CDM tip view demonstrating the actuation cables and the FBG sensor.
Fig. 4.
Fig. 4.
Block diagram for the closed-loop system.
Fig. 5.
Fig. 5.
RCM constraint and the prism approximation with arbitrary number of faces (e.g. n=6), approximating the RCM allowed region
Fig. 6.
Fig. 6.
(a) Force testing experimental setup, (b) close-up view demonstrating the force sensor and the CDM, (c) end-effector force testing result during exertion of out-of-plane distal-end force.
Fig. 7.
Fig. 7.
Comparison of the ground truth CDM tip position from the optical tracker and the estimation from the FBG data-driven approach in (a) direction Z; (b) direction X; (c) in 2-D plane; (d) system (CDM and robot) feedback accuracy (CDM TPE error with respect to the base of the entire system)
Fig. 8.
Fig. 8.
(a) Controller performance in reaching the seven corners of a 100 mm edge cube in space as goal points; (b) controller position error when reaching the cube corners (order of traced edges shown in (a)).
Fig. 9.
Fig. 9.
Controller performance in tracing a digitized circle behind the cup with constraints inactive (left figures) and active (right figures). (a) and (b) the desired cutting trajectory and the tracked CDM tip position; (c) and (d) CDM tip distance from the target points during cutting; (e) and (f) the generated task-space velocity.
Fig. 10.
Fig. 10.
Workspace comparison between the conventional rigid-tool and the proposed robotic system in less-invasive treatment of osteolysis. Numbers indicate the state of the CDM behind the cup at workspace boundary points.
Fig. 11.
Fig. 11.
The cutting performance for saw-bone phantom PCF 10 (top row) and PCF 15 (bottom row). (a) and (e) the desired cutting trajectory and the tracked CDM tip position; (b) and (f) the generated task-space velocity; (c) and (g) CDM tip distance from the target points during cutting; (d) and (h) the resulting cutting trajectory on the surface for the two phantoms.
Fig. 12.
Fig. 12.
Snapshots of the CDM insertion into the acetabular cup component and cutting of the PCF 10 saw-bone phantom based on the planned trajectory.
See this image and copyright information in PMC

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