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Research Papers

Nonlinear Bilateral Adaptive Impedance Control With Applications in Telesurgery and Telerehabilitation

[+] Author and Article Information
Mojtaba Sharifi

Department of Mechanical Engineering,
Sharif University of Technology,
Azadi Street,
Tehran 11155-9567, Iran
e-mail: mojtaba_sharifi@mech.sharif.edu

Saeed Behzadipour

Department of Mechanical Engineering,
Djawad Movaffaghian Research Center
in Neuro-Rehab Technologies,
Sharif University of Technology,
Azadi Street,
Tehran 11155-9567, Iran
e-mail: behzadipour@sharif.edu

Hassan Salarieh

Department of Mechanical Engineering,
Sharif University of Technology,
Azadi Street,
Tehran 11155-9567, Iran
e-mail: salarieh@sharif.edu

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received June 21, 2015; final manuscript received February 26, 2016; published online July 27, 2016. Assoc. Editor: Hashem Ashrafiuon.

J. Dyn. Sys., Meas., Control 138(11), 111010 (Jul 27, 2016) (16 pages) Paper No: DS-15-1282; doi: 10.1115/1.4033775 History: Received June 21, 2015; Revised February 26, 2016

A bilateral nonlinear adaptive impedance controller is proposed for the control of multi-degrees-of-freedom (DOF) teleoperation systems. In this controller, instead of conventional position and/or force tracking, the impedance of the nonlinear teleoperation system is controlled. The controller provides asymptotic tracking of two impedance models in Cartesian coordinates for the master and slave robots. The proposed bilateral controller can be used in different medical applications, such as telesurgery and telerehabilitation, where the impedance of the robot in interaction with human subject is of great importance. The parameters of the two impedance models can be adjusted according to the application and corresponding objectives and requirements. The dynamic uncertainties are considered in the model of the master and slave robots. The stability and the tracking performance of the system are proved via a Lyapunov analysis. Moreover, the adaptation laws are proposed in the joint space for reducing the computational complexity, however, the controller and the stability proof are all presented in Cartesian coordinates. Using simulations on a 2DOF robot, the effectiveness of the proposed controller is investigated in telesurgery and telerehabilitation operations.

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Figures

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Fig. 1

A schematic diagram of teleoperation systems consisting of a master robot, a slave robot, a human operator, an environment, and the communication channels

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Fig. 2

The signal transmissions in the proposed bilateral controller with three communication channels

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Fig. 3

The haptic sense of the human operator using the master impedance model (9)

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Fig. 4

The concepts of the master and slave impedance models in the proposed bilateral control strategy

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Fig. 5

The structure of the bilateral adaptive impedance controller

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Fig. 6

The 2DOF robot manipulator with revolute and prismatic joints used for the evaluation of the proposed controller

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Fig. 7

Interaction forces between the surgeon and master (fh) and between the slave and soft tissue environment (fe) in x direction

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Fig. 8

The force-tracking error (fh−kffe) in x direction

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Fig. 9

Position, velocity, and acceleration of the master and slave robots together with their impedance model responses in x direction

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Fig. 10

The absolute position-tracking errors in x−z plane: the master error with respect to its impedance model ‖xm−xmodm‖2 (dashed line), the slave error with respect to its impedance model ‖xs−xmods‖2 (dashed–dotted line), and the error between master and slave ‖xs−kpxm‖2 (solid line)

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Fig. 11

The convergence of master and slave error dynamics ‖Sm‖2 and ‖Ss‖2 to the sliding surfaces Sm=0 and Ss=0 in less than 1 s

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Fig. 12

The actual and estimation values of the master acceleration (x¨m and x¨m est) together with their difference (estimation error Δx¨m=x¨m est−x¨m) in x direction, where the master acceleration is estimated by Eq. (12)

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Fig. 13

The estimation of ten dynamic parameters for (a) master and (b) slave

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Fig. 14

The value of the master and slave forgetting factors βm(t) and βs(t)

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Fig. 15

Interaction forces between the therapist and the master robot (fh) and between the slave and the patient (fe) in z direction

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Fig. 16

The force-tracking error (fh−kffe) in z direction

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Fig. 17

Position, velocity, and acceleration of the master and slave robots together with their impedance model responses in z direction

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Fig. 18

The absolute position-tracking errors in x–z plane: the master error with respect to its impedance model ‖xm−xmodm‖2 (dashed line), the slave error with respect to its impedance model ‖xs−xmods‖2 (dashed–dotted line), and the error between master and slave ‖xs−kpxm‖2 (solid line)

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Fig. 19

Position- and force-tracking performance together with master acceleration estimation during the intermittent contact with a hard tissue, the contact starts at t=0.88 s when the slave end-effector reaches the surface of the tissue (ze=0.66  m) and ends at t=5.37 s

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