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Shape Sensing of Variable Stiffness Soft Robots using Electrical Impedance Tomography

Authors :
George P. Mylonas
Mark Runciman
Ara Darzi
James Avery
Howard, A
Althoefer, K
Arai, F
Arrichiello, F
Caputo, B
Castellanos, J
Hauser, K
Isler, V
Kim, J
Liu, H
Oh, P
Santos, V
Scaramuzza, D
Ude, A
Voyles, R
Yamane, K
Okamura, A
National Institute for Health Research
Source :
ICRA, International Conference on Robotics and Automation (ICRA)
Publication Year :
2019
Publisher :
arXiv, 2019.

Abstract

Soft robotic systems offer benefits over traditional rigid systems through reduced contact trauma with soft tissues and by enabling access through tortuous paths in minimally invasive surgery. However, the inherent deformability of soft robots places both a greater onus on accurate modelling of their shape, and greater challenges in realising intraoperative shape sensing. Herein we present a proprioceptive (self-sensing) soft actuator, with an electrically conductive working fluid. Electrical impedance measurements from up to six electrodes enabled tomographic reconstructions using Electrical Impedance Tomography (EIT). A new Frequency Division Multiplexed (FDM) EIT system was developed capable of measurements of 66 dB SNR with 20 ms temporal resolution. The concept was examined in two two-degree-of-freedom designs: a hydraulic hinged actuator and a pneumatic finger actuator with hydraulic beams. Both cases demonstrated that impedance measurements could be used to infer shape changes, and EIT images reconstructed during actuation showed distinct patterns with respect to each degree of freedom (DOF). Whilst there was some mechanical hysteresis observed, the repeatability of the measurements and resultant images was high. The results show the potential of FDM-EIT as a low-cost, low profile shape sensor in soft robots.<br />Comment: Fixed PDF conversion error. Now published in ICRA 2019, IEEE International Conference on Robotics and Automation 2019

Details

Database :
OpenAIRE
Journal :
ICRA, International Conference on Robotics and Automation (ICRA)
Accession number :
edsair.doi.dedup.....0722c3f19afe5aecbdfbde14fb9bbda7
Full Text :
https://doi.org/10.48550/arxiv.1904.02429