Shape Sensing of Variable Stiffness Soft Robots using Electrical Impedance Tomography
This addresses the problem of accurate shape modeling for soft robots in minimally invasive surgery, offering a low-cost, low-profile sensing solution, though it appears incremental as it builds on existing EIT methods.
The paper tackled the challenge of intraoperative shape sensing in soft robots by developing a proprioceptive soft actuator using Electrical Impedance Tomography (EIT) with a new Frequency Division Multiplexed system, achieving 66 dB SNR and 20 ms temporal resolution to infer shape changes in two actuator designs.
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.