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Comparing the transparency of the haptic paddle using different interaction controllers

Ramon Rohner, Xiaowei Lin

23th December 2021, Zurich

Physical Human Robot Interaction Specialization Project

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Introduction - Background and Motivation

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  • Background and Motivation
    • Robotic devices are widely used in neurological rehabilitation
    • Different impairment levels of patients
    • Providing the right amount of support and challenge
    • Impedance control(detailed block diagrams in the backup slides)
      • open-loop impedance control
      • impedance control with model feedforward
      • Impedance control with force feedback

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Low impedance

Almost no resistance to motion (Z → 0)

High impedance

Almost complete resistance to motion (Z → ∞)

pHRI Lecture 10

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Introduction - Problem Statement

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  • Transparency Mode
    • Transparency mode is when we can freely move the device with less effort
    • Moving the the uncontrolled device requires forces (inherent friction and inertias)
    • May not be suitable for neurologically impaired patients (reduced motor function) or to train fine motor skills.
    • To achieve a Transparency Mode behavior (Zapp → 0 or moving hand through air) a force feedback can be implemented

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wdrfree.com

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Introduction - Problem Statement

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  • Transparency Planes
    • Transparency planes are three dimensional plots
    • Allow a comparison of the lower apparent impedance boundaries of a haptic device

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Metzger et al. (2015)

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Methods - Implementation

  • Tachometer Characterization - Transfer Function

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Datasheet Tachometer DC Tacho DCT 22 0.52 Volt

pHRI Lecture 8

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Methods - Implementation

  • Tachometer Characterization - Performance Comparison

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Methods - Implementation

  • Tachometer Characterization - Performance Comparison

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Methods - Implementation

  • Force Sensor Characterization

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Methods - Implementation

  • Force Feedback Implementation in Transparency Mode

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Results - Videos

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Uncontrolled

Friction-Gravity Compensation

Force Feedback

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Results - Transparency Planes

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I_app

[kg*m^2]

b_app

[Nm/(rad/s)]

R-square

# fitting points

Max. residual

[Nm]

Avg. residual

[Nm]

Uncontrolled

0.0007852

0.008958

0.8852

5039

0.0218

0.0049

Friction and Gravity Compensated

0.0008166

0.005411

0.8842

4224

0.0335

0.0080

Force Feedback

0.0005468

0.004377

0.9139

4665

0.0262

0.0076

Fitting Results

Control Schemes

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Discussion

  • Transparency Planes Comparison

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Discussion

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I_app

[kg*m^2]

b_app

[Nm/(rad/s)]

R-square

# fitting points

Max. residual

[Nm]

Avg. residual

[Nm]

Uncontrolled

0.0007852

0.008958

0.8852

5039

0.0218

0.0049

Friction and Gravity Compensated

0.0008166

0.005411

0.8842

4224

0.0335

0.0080

Force Feedback

0.0005468

0.004377

0.9139

4665

0.0262

0.0076

Metzger et al. (2015)

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Fitting Results

Control Schemes

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Discussion

Physical Human Robot Interaction Specialization Project

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Control Schemes

Metzger et al. (2015)

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Apparent mass: 32 kg

Apparent inertia: 0.0007852 kg*m^2

Apparent dampening: 141 N/(m/s)

Apparent dampening: 0.008958 Nm/(rad/s)

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Discussion

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Control Schemes

Metzger et al. (2015)

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Apparent mass: 0.8 kg

(32 kg uncontrolled)

Apparent inertia: 0.0005468 kg*m^2

(0.0007852 kg*m^2 uncontrolled)

Apparent dampening: 2.7 N/(m/s)

(141 N/(m/s) uncontrolled)

Apparent dampening: 0.004377 Nm/(rad/s)

(0.008958 Nm/(rad/s) uncontrolled)

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Limitations

  • The non-linear friction and gravity we did not perfectly compensate
  • The inconsistent behaviour of the force sensor
  • The right feedback gain for the force feedback

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Conclusion and Outlook

  • Conclusion
    • ImpC with force feedback does improve the performance of the haptic paddle
    • But not always…

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  • Outlook
    • Better modeling of friction and gravity
    • Force sensor
    • Method to find the better gain for the force feedback

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References

  • J.-C. Metzger, O. Lambercy, and R. Gassert, "Performance comparison of interaction control strategies on a hand rehabilitation robot," 2015 2015: IEEE, doi: 10.1109/icorr.2015.7281308. [Online]. Available: https://dx.doi.org/10.1109/icorr.2015.7281308
  • J.-C. Metzger, O. Lambercy, and R. Gassert, "High-fidelity rendering of virtual objects with the ReHapticKnob - novel avenues in robot-assisted rehabilitation of hand function," 2012 2012: IEEE, doi: 10.1109/haptic.2012.6183769. [Online]. Available: https://dx.doi.org/10.1109/haptic.2012.6183769
  • O. Lambercy, “Physical Human Robot Interaction”, Lecture Notes, ETHZ, 2021
  • J. Dittli, “Physical Human Robot Interaction”, Lecture Notes, ETHZ, 2021
  • R. Gassert, “Physical Human Robot Interaction”, Lecture Notes, ETHZ, 2020

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Ramon Rohner

rarohner@student.ethz.ch

Xiaowei Lin

xiaoweilin@student.ethz.ch

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Physical Human Robot Interaction Specialization Project 07

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ETH Zurich

NO, Clausiusstrasse 2-30

8006 Zurich, Switzerland

Thank you for your attention!

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Introduction - Problem Statement - Backup Slides

  • Interaction Control Scheme
    • Open-loop Impedance Control

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    • Impedance Control with Model Feedforward

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Introduction - Problem Statements - Backup Slides

  • Interaction Control Scheme
    • Impedance Control with Force Feedback

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