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Suturing in Confined Spaces: Constrained Motion Control of a Hybrid 8-DoF Robot

Suturing in Confined Spaces: Constrained Motion Control of a Hybrid 8-DoF Robot Ankur Kapoor 1 , Nabil Simaan 2 , Russell H. Taylor 1 1 ERC-CISST Department of Computer Science Johns Hopkins University 2 ARMA: Advanced Robotics & Mechanism Applications

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Suturing in Confined Spaces: Constrained Motion Control of a Hybrid 8-DoF Robot

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  1. Suturing in Confined Spaces: Constrained Motion Control of a Hybrid 8-DoF Robot Ankur Kapoor1, Nabil Simaan2, Russell H. Taylor1 1 ERC-CISST Department of Computer Science Johns Hopkins University 2 ARMA: Advanced Robotics & Mechanism Applications Department of Mechanical Engineering Columbia University

  2. “Master” “Slave” Patient Patient Throat Controller Control for Robot-assisted MIS of the Throat • This paper is about • Kinematic modeling 8 DoF hybrid robot • High level real-time control algorithm for suturing • Experimental validation

  3. Previous Works: Surgical Dexterity Enhancement • Commercial Systems • Zeus • Intuitive Surgical Da-Vinci (Endo-Wrist) • Research Works • Dario (3 mm SMA for arthroscopy visualization) • Ikuta (15 mm SMA, colonoscopy) • Ikuta, Yamamoto, Sasaki (Deep surgical field) • Fujie (Dexterity for Brain Surgery) • Asai & Mituishi (5mm snake like device for microsurgery) • Salisbury & Intuitive Surgical (Endo-Wrist, 5 mm wire actuated snake) • Sastry & Cavusoglu (2-3 DoF ~8mm wrists) • Jan Peirs (5 mm wire actuated snake) • ….. And many other works

  4. Previous Work: Control • Redundancy resolution [Yoshikawa, Nakamura et al, Hirose, Klein et al.] • Hyper-redundant robots [Chirikjian et al, Angeles & Zanganeh] • Constrained control [Funda et al]

  5. endoscope instrument (tissue shaver) laryngoscope (cannula for instruments) Surgical Setup in Throat MIS* *Courtesy of Paul Flint M.D. Johns Hopkins School of Medicine

  6. View limited by soft tissue Haptic information deficiency Hand-eye coordination Multiple tools Long rigid instruments Predetermined entry port No distal dexterity 4 DoF motion constraint No suturing or functional tissue reconstruction capability Limitations of the Surgical Setup

  7. Dexterous Slave for Confined Spaces electrical supply /data lines snake drive unit fast clamping device tool manipulation unit (TMU) rotating base base link laryngeoscope DDU holder DDU for saliva suction distal dexterity unit (DDU) Snake & parallel unit

  8. The Snake-Like Units (SLU) 27.6mm “Large Snake” 4mm “Small Snake” Previous works: Walker & Gravange: snakes using a single flexible backbone & wire actuation

  9. enddisk movingplatform spacerdisk centralbackbone basedisk internal wire DDUholder Quick connect mechanism Snake-likeunit Parallel Manipulation Unit The Distal Dexterity Unit (DDU) Can be used for: suturing, suction, light, visualization, drug delivery….. Simple and cheap to fabricate. No backlash. Actuation redundancy.

  10. Center line of wound Ideal Path Needle radius Exit Point Entry Point Tissue surface Suture needle, typical length 1/2 or 3/8 circle Problem Statement: Task Model for Suturing • Suture needle is circular with known radius • Attached to SLU such that • Needle plane is parallel • Center of the needle lies along • Ideal path

  11. Gripper optical marker body OptoTrak – for optical position measurements Snake-Like Unit (SLU) LARS – A 6-DoF Robot Reference optical marker body Our experimental setup

  12. Kinematics of LARS • A 6-DoF serial chain • Has a “remote center of motion” • Kinematics similar to proposed design

  13. Kinematics of DDU where We assume a constant bending model, i.e Angles L and related to backbone lengths by Simaan N. et al, “A Dexterous System for Laryngeal Surgery,” ICRA 2004

  14. Redundancy Resolution for Suturing = Augmented state vector (LARS + Snake) = Configuration vector of the SLU = Joint variables of the SLU Optimization formula Incremental motion User’s input Geometric constraints for task frame(s) Reference direction/ target Move the Robot Task frame(s) info

  15. Minimizing tissue tear • We want… Satisfy suturing task Needle center errors

  16. Minimizing tissue tear • A linear approximation… where Unit vector in sphere with radius εg

  17. Minimizing tissue tear where

  18. Avoiding joint speed limits • SLU has actuators with limited power • Limits the max. speed of actuations • We want… • Matrix representation where

  19. Avoiding joint limits • Finally we want… • In addition we want… • Matrix representation where s.t.

  20. Optimization Algorithm Step 1: Describe a desired incremental motion of the instrument based on user's inputs. Step 2: Use the robot instantaneous kinematic equations to produce a linearized optimization problem, Step 3: Use known numerical methods to compute incremental joint motions and use these results to move the robot. [Lawson and Hanson’s method] Step 4: Go back to Step 1.

  21. Comparing Proximal Joint Motion Joint Motion less than 5x10-8mm Max Joint Motion around 20mm Distal dexterity provided by SLU helps in avoiding proximal joint motion during suturing

  22. Results – Actual vs Ideal Paths Using Robot Encoders and Kinematics Center of Suture with a sphere of 1.4um Center line of wound Ideal Path Needle radius Exit Point Entry Point Tissue surface Suture, typical length 1/2 or 3/8 circle

  23. Results – External Measurements Using OptoTrak - Optical Measuring Device Center of Suture with a sphere of 1.84mm Gripper optical marker body OptoTrak – for optical position measurements Snake-Like Unit (SLU) LARS – A 6-DoF Robot Reference optical marker body

  24. Results - Movie

  25. Future Work Suturing using the “Steady Hand Robot” To appear in Intl. Conf. on Medical Image Computing and Computer Assisted Intervention, CA, USA, Oct 2005

  26. Conclusions • Developing and testing the high-level control for a future tele-robotic system for MIS of the throat and upper airways. • Extendable to include additional constraints such as collision avoidance, anatomic-based constraints [Li ‘03] • Suturing motion can be accomplished with minimal motion of proximal joints if SLU is used. • Validation of kinematic model of SLU. Li ’05: Li M., and Taylor R. H., Spatial Motion Constraints in Medical Robot Using Virtual Fixtures Generated by Anatomy, ICRA, 2003

  27. Acknowledgements • NSF grant #IIS9801684 • NSF grant #EEC9731478 • Johns Hopkins University • Paul Flint, Johns Hopkins School of Medicine • Peter Kazanzides • Ming Li

  28. Questions?

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