Modelling Of Uniaxial Egain-Based Strain Sensors For Proprioceptive Sensing Of Soft Robots

2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)(2019)

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摘要
Soft strain resistive sensors based on eutectic gallium-indium liquid metal can play an important role in proprioceptive sensing for soft robots. However, there are no available mathematical models to accurately estimate the strain as a function of the measured resistance. Furthermore, non-uniform strain in the microchannels has not been analysed yet. In this paper, we introduce a new model to estimate the strain or elongation in sub-millimetre scale, and analyse its accuracy through a customised testing set-up and procedure. The effect of strain rate on the measurement accuracy is also studied. We compare existing theoretical models with our experimental results, and discuss the differences between them. Moreover, we analyse the effect of strain rate on hysteresis caused by the viscoelastic behaviour and introduce a new model for it to be potentially used for future work. This paper demonstrates, among other things, that rational models could provide high accuracy in strain estimation, and might help to enhance proprioceptive sensing and state control of soft robots.
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关键词
strain estimation,rational models,measurement accuracy,strain rate,customised testing,nonuniform strain,measured resistance,mathematical models,eutectic gallium-indium liquid metal,soft strain resistive sensors,soft robots,proprioceptive sensing,uniaxial EGaIn-based strain sensors
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