LAUSR

Twisted string actuators (TSAs) have exhibited great promise in robotic applications by generating high translational force with low input torque. Despite great success, it remains a challenge to reliably estimate the strain of TSAs using compact solutions while maintaining actuator compliance. The inclusion of position sensors not only increases system complexity but also decreases system compliance, a property often crucial in soft robots. We recently constructed a compliant TSA with self-sensing capability by adopting conductive and stretchable super-coiled polymer (SCP) strings; however, only quasi-static measurements of the strain-resistance correlation were obtained. This study proposes a strategy to experimentally characterize and model the transient self-sensing property in compliant TSAs. The correlation between resistance and strain is characterized under different motor twisting sequences and step durations, and exhibited transient decay, hysteresis, and creep. A self-sensing model that consists of a log-based nonlinear term, a rate-dependent Prandtl-Ishlinskii hysteresis term, and a creep term is proposed for the compliant TSAs. Experimental results confirm the high effectiveness of the proposed self-sensing approach, with the average model validation error less than 0.036 cm.