Parametric analysis of multi-material soft sensor structures for enhanced strain sensitivity

Abstract

Soft strain sensors that utilize geometrical changes of elastomer structures embedded with conductive liquid have advantage of physical compliance and dynamic durability. Approaches to enhancing their sensitivities are however limited, since the output resistance is dependent only on the single input, i.e., strain. In this paper, a multi-material strain sensor structure is proposed to overcome the limitation in improving the sensitivity. We define two design parameters that determine the strain sensitivity: the stiffness ratio and the length portion of the different materials used in the structure. Investigations on the effects of the parameters on the sensor performances, including the sensitivity, the stiffness, the resolution, the hysteresis, the linearity, the durability, and the maximum strain, are conducted by deriving a global mathematical model validated through experiments. Based on the results, there exists the optimal length portion of the component materials that maximizes the sensitivity, depending on the stiffness of each material component. We demonstrate an example, using the optimized parameters, of a multi-material sensor with the highest resolution three times that of a conventional single-material sensor. We also demonstrate that the high precision achieved in the proposed multi-material sensor structure enables successful measurement of the tiny movements of a human finger. Lastly, potential design improvements are provided so that the structure can further enhance its structural integrity and compliance.