Bioinspired Rheological Sensing for Robotic Liquid Identification in Sealed Containers via Ultrafast Incipient Slip Detection.

Abstract

The rapid, non-invasive identification of sealed liquids is crucial for ensuring counter-terrorism security and improving operational efficiency in various scenarios such as airports and large-scale events. Existing technologies are limited by invasive procedures or reliance on vision. In this research, we developed a bioinspired iontronic tactile sensor with an interlocked "protrusion-groove" structure. Its unique biomimetic structure allows for the detection of static pressure and incipient slip within a single device, with a peak sensitivity of up to 1873.83 kPa^- ¹ in the low-pressure regime and a slip response time as fast as 46 ms. A robotic fingertip integrated with this sensor can effectively capture the transient signals generated by shaking liquids. Furthermore, by extracting physical features from the signals and applying a Random Forest classifier, we developed a non-visual liquid identification system that achieves an accuracy of 99.04% ± 0.47% for different liquids. This work provides a practical solution for non-visual liquid identification and demonstrates a robust approach for enabling robots to achieve multimodal tactile perception.