In recent years, the inverse pneumatic artificial muscles attained great attention in soft robotics, especially for the wider motion range compared to traditional positive pneumatic actuators. Besides self-sensing is a recognized highly desirable property for soft actuators to enable proprioception and to facilitate the soft robots control, a self-sensing strategy for a soft inverse pneumatic muscle was still missing. In this paper, we present the first self-sensing inverse pneumatic artificial muscle in which the reinforcing but compliant element that guides the actuator motion during actuation has not only a mechanical function but, being also electrically conductive, it endows the actuator with self-sensing. Here, the actuator design and manufacturing are described, together with an electro- mechanical characterization. In addition, we demonstrate its self-sensing capability in a dynamic setting, by predicting the actuator strain from its electric resistance variation, through a calibration model.

A Self-sensing Inverse Pneumatic Artificial Muscle

Lucrezia Lorenzon
;
Martina Maselli;Matteo Cianchetti
2022-01-01

Abstract

In recent years, the inverse pneumatic artificial muscles attained great attention in soft robotics, especially for the wider motion range compared to traditional positive pneumatic actuators. Besides self-sensing is a recognized highly desirable property for soft actuators to enable proprioception and to facilitate the soft robots control, a self-sensing strategy for a soft inverse pneumatic muscle was still missing. In this paper, we present the first self-sensing inverse pneumatic artificial muscle in which the reinforcing but compliant element that guides the actuator motion during actuation has not only a mechanical function but, being also electrically conductive, it endows the actuator with self-sensing. Here, the actuator design and manufacturing are described, together with an electro- mechanical characterization. In addition, we demonstrate its self-sensing capability in a dynamic setting, by predicting the actuator strain from its electric resistance variation, through a calibration model.
2022
978-1-6654-0828-8
978-1-6654-0829-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/546551
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