Abstract

Developing simple device configurations to satisfy independent thermal and force sensing is critical for improving the recognition and manipulation capabilities of robotic hands on objects, but it remains a challenge. In this paper, through the composition adjustment of polyvinyl alcohol, KOH, nano-silica, glycerin, and the microporous structure design, the prepared ionic hydrogel sensor has promising comprehensive performance. It shows thermal sensitivity (−0.47 % °C−1, 0–20 °C; −0.24 % °C−1, 20–50 °C), pressure sensitivity (1 kPa−1, 0–300 kPa), pressure detection limit of 1 Pa, and mechanical durability (1000 compression fatigue cycles at 100 kPa). More importantly, the pressure-sensitive and thermal-sensitive properties hardly interfere with each other due to the ionic hydrogel network's synergy of excellent water retention, anti-freezing properties and heat insulation ability. The multifunctional tactile sensor is integrated into a robot hand to obtain force and thermal information of the measured object, and combined with machine learning algorithms to realize object recognition. The proposed sensing scheme has been applied to 6 kinds of fruit and vegetable classification tasks in a cold chain logistics scenario, showing a classification accuracy of 95 %.

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