Force-Sensorless Identification and Classification of Tissue Biomechanical Parameters for Robot-Assisted Palpation
<p>Experimental setup: <span class="html-italic">3D Systems Omni Touch</span> robot, <span class="html-italic">ATI Nano 17</span> force sensor (only for validation), and the silicone samples <span class="html-italic">Ecoflex Gel</span>, <span class="html-italic">Ecoflex 00-50</span>, <span class="html-italic">Dragon Skin 10</span>, and <span class="html-italic">Dragon Skin 30</span> silicone samples.</p> "> Figure 2
<p>Force tracking and estimation for the Ecoflex 00-50 sample. (<b>a</b>) Forces: desired (- - -), measured (<span style="color:red">—</span>), and estimated (<span style="color:blue">—</span>). (<b>b</b>) Force tracking error. (<b>c</b>) Force estimation error.</p> "> Figure 3
<p>Measured displacement of the tissue for the Eco Flex 00-50 sample.</p> "> Figure 4
<p>Estimation of the linear elasticity coefficients <math display="inline"><semantics> <msub> <mi>k</mi> <mi mathvariant="normal">l</mi> </msub> </semantics></math> in model (<a href="#FD3-sensors-22-08670" class="html-disp-formula">3</a>) for the four different rubber samples and their normal probability density functions.</p> "> Figure 5
<p>Estimation of the nonlinear elasticity coefficients <math display="inline"><semantics> <msub> <mi>k</mi> <mi>nl</mi> </msub> </semantics></math> in model (<a href="#FD4-sensors-22-08670" class="html-disp-formula">4</a>) for the four different rubber samples and their normal probability density functions.</p> ">
Abstract
:1. Introduction
- Simultaneous estimation of robot end-effector forces and velocities, using only joint position sensors and commanded torques.
- Estimation of tissues’ biomechanical parameters based on the estimated forces and velocities.
- A standard robot manipulator model is employed instead of an ad hoc system.
- Classification of tissues is based on the estimated parameters taking into account a linear model, a nonlinear model, and the combination of both models, giving, as a result, a better classification for the last case.
2. Materials and Methods
2.1. Robot and Environment Model
2.2. Velocity and Force Observer
2.3. Parameter Estimation
2.4. Closed-Loop Force Control
2.5. Tissue Classification
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
FTO | Finite-Time Observer |
BC | Bayesian Classifier |
SBC | Simple Bayesian Classifier |
Appendix A. Dyamic Model and Parameters for the Touch Manipulator
Parameter | Estimated Value |
---|---|
0.00027632 | |
0.00056422 | |
0.00084797 | |
0.01706838 | |
0.01920879 | |
0.01622868 | |
0.00357954 | |
0.00551499 |
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Parameter | ||||
---|---|---|---|---|
Ecoflex Gel | 0.2274 | 0.0047 | 0.013 | |
Ecoflex 00-50 | 0.4899 | 0.1101 | ||
Dragon Skin 10 | 0.5158 | 0.1313 | ||
Dragon Skin 30 | 0.7377 | 0.3688 |
Parameter | ||||
---|---|---|---|---|
Ecoflex Gel | 0.0191 | 0.0016 | 0.0013 | |
Ecoflex 00-50 | 0.0314 | 0.0051 | ||
Dragon Skin 10 | 0.0364 | 0.0051 | ||
Dragon Skin 30 | 0.0507 | 0.0089 |
Material | Ecoflex Gel | Ecoflex 00-50 | Dragon Skin 10 | Dragon Skin 30 |
% Correct class. | 100 | 50 | 50 | 100 |
Material | Ecoflex Gel | Ecoflex 00-50 | Dragon Skin 10 | Dragon Skin 30 |
% Correct class. | 100 | 96.88 | 100 | 100 |
Material | Ecoflex Gel | Ecoflex 00-50 | Dragon Skin 10 | Dragon Skin 30 |
% Correct class. | 100 | 100 | 100 | 100 |
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Gutierrez-Giles, A.; Padilla-Castañeda, M.A.; Alvarez-Icaza, L.; Gutierrez-Herrera, E. Force-Sensorless Identification and Classification of Tissue Biomechanical Parameters for Robot-Assisted Palpation. Sensors 2022, 22, 8670. https://doi.org/10.3390/s22228670
Gutierrez-Giles A, Padilla-Castañeda MA, Alvarez-Icaza L, Gutierrez-Herrera E. Force-Sensorless Identification and Classification of Tissue Biomechanical Parameters for Robot-Assisted Palpation. Sensors. 2022; 22(22):8670. https://doi.org/10.3390/s22228670
Chicago/Turabian StyleGutierrez-Giles, Alejandro, Miguel A. Padilla-Castañeda, Luis Alvarez-Icaza, and Enoch Gutierrez-Herrera. 2022. "Force-Sensorless Identification and Classification of Tissue Biomechanical Parameters for Robot-Assisted Palpation" Sensors 22, no. 22: 8670. https://doi.org/10.3390/s22228670