Abstract

The twisted and coiled polymer muscle (TCPM) has two major benefits: low weight and low cost. Therefore, this new type of actuator is increasingly used in robotic applications where these benefits are relevant. Closed-loop control of these muscles, however, requires additional sensors that add weight and cost, negating the muscles' intrinsic benefits. Self-sensing enables feedback without added sensors. In this article, we investigate the feasibility of using self-sensing in closed-loop control of a Joule-heated muscle. We use a hardware module that is capable of driving the muscle, and simultaneously providing sensor measurements based on inductance. A mathematical model relates the measurements to the deflection. In combination with a simple force model, we can estimate both deflection and force, and control either of them. For a muscle that operates within deflections of [10, 30] mm and forces of [0.32, 0.51] N, our self-sensing method exhibited a 95% confidence interval of 2.14 mm around a mean estimation error of -0.27 mm and 29.0 mN around a mean estimation error of 7.5 mN, for the estimation of, respectively, deflection and force. We conclude that self-sensing in closed-loop control of Joule-heated TCPMs is feasible and may facilitate further deployment of such actuators in applications where low cost and weight are critical.

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