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@inproceedings{Avery:2019:10.1109/ICRA.2019.8793862,
author = {Avery, J and Runciman, M and Darzi, A and Mylonas, GP},
doi = {10.1109/ICRA.2019.8793862},
pages = {9066--9072},
publisher = {IEEE},
title = {Shape sensing of variable stiffness soft robots using electrical impedance tomography},
url = {http://dx.doi.org/10.1109/ICRA.2019.8793862},
year = {2019}
}
TY - CPAPER
AB - 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.
AU - Avery,J
AU - Runciman,M
AU - Darzi,A
AU - Mylonas,GP
DO - 10.1109/ICRA.2019.8793862
EP - 9072
PB - IEEE
PY - 2019///
SN - 1050-4729
SP - 9066
TI - Shape sensing of variable stiffness soft robots using electrical impedance tomography
UR - http://dx.doi.org/10.1109/ICRA.2019.8793862
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000494942306095&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - https://ieeexplore.ieee.org/document/8793862
UR - http://hdl.handle.net/10044/1/79679
ER -
