Presentation Transcript
Telemanipulation of Snake-Like Robots forMinimally Invasive Surgery of the Upper Airway : Telemanipulation of Snake-Like Robots for Minimally Invasive Surgery of the Upper Airway Ankur Kapoor1, Kai Xu2, Wei Wei2
Nabil Simaan2 and 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
Slide2 : *Courtesy of Paul Flint M.D. Johns Hopkins School of Medicine Surgical Setup in Throat MIS*
Limitations of the Surgical Setup : Limitations of the Surgical Setup motion constraint No distal dexterity Hand-eye coordination Long rigid instruments Predetermined entry port No suturing or functional tissue reconstruction capability
Human-machine cooperative manipulation in surgery : Display atlases Manipulation enhancement Online references & decision support Cooperative control and “macros” atlases
libraries Human-machine cooperative manipulation in surgery Situation assessment
Task strategy & decisions
Sensory-motor coordination Sensors HMCS System
Related Works:Surgical Dexterity Enhancement : Related 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
Related Works: Virtual Fixtures : Related Works: Virtual Fixtures Virtual fixtures: perceptual overlays designed to enhance performance
Active Compliance
Rosenberg
Stanisic et al.
Davies et al.
Park et al.
Vision Based
Marayong et al.
Dewan et al.
Based on Constrained Control
Funda et al.
Li et al.
Snake-Like Units (SLU) : Snake-Like Units (SLU) Uses push-pull superelastic backbones & actuation redundancy
Eliminates dependency on precision joints & backlash
Simple to manufacture
Easily downs-scalable to smaller diameters
Enhanced force application capability Simaan N. et al, MICCAI 2004, ICRA 2004, ICRA 2005
High Level Constrained ControlSteady Hand Robot : High Level Constrained Control Steady Hand Robot Handle Force Kv Joint Velocities Registered Model Current State Constraint Generation Optimization Framework Low Level Controller
5 Basic Geometric Constraints(Virtual fixture library) : 5 Basic Geometric Constraints (Virtual fixture library) Kapoor, A. Li, M., Taylor, R.H. Constrained Control for Surgical Assistant Robots, ICRA 2006 Optimization Framework
Snake Like RobotSystem Architecture :
x2 (Left & Right)
x2 (Left & Right) Snake Like Robot System Architecture Low Level Controller High Level Controller Low Level Controller High Level Controller
Master Side Low-Level Controller : Master Side Low-Level Controller The low-level is a PD Joint Controller
The force applied by user is treated as disturbance
Under quasi-static approximation, position error is proportional to user force Set Point User Force Encoder Position
Master Side High-Level Controller : Master Side High-Level Controller A constrained least squares problem is solved for joint velocities.
Objective function determines the desired outcome.
Constraints modify the behavior of the robot to a given input. Joint Velocities Slave Frame Master Frames
Master Side High-Level Controller : Master Side High-Level Controller Objectives:
Minimize error between desired motion and actual motion
Oppose motion that increases master-slave tracking error
Minimize the extraneous motion of the joints, and
Avoid large incremental joint motions that could occur near singularities
Master Side High-Level Controller : Master Side High-Level Controller Objectives:
Minimize error between desired motion and actual motion
Oppose motion that increases master-slave tracking error
Minimize the extraneous motion of the joints, and
Avoid large incremental joint motions that could occur near singularities
Master Side High-Level Controller : Master Side High-Level Controller Objectives:
Minimize error between desired motion and actual motion
Oppose motion that increases master-slave tracking error
Minimize the extraneous motion of the joints, and
Avoid large incremental joint motions that could occur near singularities
Master Side High-Level Controller : Master Side High-Level Controller Constraints:
General form: Hm,j¢qm ¸ hm,j
Not allow motion outside joint range
Not allow motion that exceeds joint velocity limits
Additional constraints can be added from the VF Library
Slave Side Low-Level Controller : Slave Side Low-Level Controller The low-level is a PID Joint Controller
The two DOF of each snake are parameterized by two angles
The bending angle of primary backbone
The orientation of bending plane with respect to base XZ plane Set Point Slave Frame
Slave Side High-Level Controller : Slave Side High-Level Controller Objectives:
Minimize error between desired motion and actual motion
Minimize the extraneous motion of the joints, and
Avoid large incremental joint motions that could occur near singularities Constraints:
Not allow motion outside joint range
Not allow motion that exceeds joint velocity limits
More constraints can be added from the VF Library
Experimental SetupMaster : Experimental Setup Master
Experimental SetupSlave : Experimental Setup Slave
Experimental SetupRoll motion : Experimental Setup Roll motion
Experimental SetupS-bend motion : Experimental Setup S-bend motion
Experimental SetupSurgeon’s view : Experimental Setup Surgeon’s view
Experimental SetupFish Hook : Experimental Setup Fish Hook
Conclusion : Conclusion A novel system designed considering special requirements for MIS of throat
High-level control of a telesurgical system
Efficient use of dexterity avoids motion of proximal joints
Validation experiments using suturing phantom
Acknowledgements : Acknowledgements Dr. Paul Flint, School of Medicine, Johns Hopkins University.
NSF Research Grant #EEC9731478 and #IIS9801684
NIH #R21 – B004457-01
Johns Hopkins and Columbia University Internal Funds
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