Over a long period of time, arthropods evolve to have two excellent mechanical sensilla of slit sensilla and trichobothria sensilla, which construct a perfect perception system. The former mainly perceives the change of the in-the-plane force while the latter perceives that of the out-of-plane force. In recent years, these two sensilla have attracted researchers as the models for developing artificial mechanical sensors. This review mainly includes the biomechanics and biomimetic manufacturing techniques as well as their future application value. In order to better understand the advantages of biological strategies, this review describes the morphology, mechanical analysis, and information recognition of slit sensilla and trichobothria sensilla. Then this review highlights the recent development of Crack-based Sensors (CBSs) and Hair-like Sensors (HLSs) based on the analysis of biological mechanism. The manufacturing method and substrate of crack in CBS and those of hair rods in HLS are discussed respectively. Finally, the practical applications and potential value of two sensilla, such as flexible wearable electronic devices, robot sensing system, autopilot sensing and wind tunnel speed detection, are briefly discussed.
Electronic skins equip robots and biomedical devices with intuitive skin‐like sensitivity. Performance‐driven design of electronic skins is a critical need for electronic or biomedical applications. Prior research primarily focuses on investigating effects of microstructures on sensor performance at low pressure ranges. However, having predictive and tunable electro–mechanical responses across an extensive pressure range (>100 kPa) is paramount. Here, the authors propose a system that virtually customizes micropyramids for e‐skin sensors. The associations between geometry parameters, material properties, and single‐pyramid performance are systematically explored via numerical simulations, empirical characterizations, and analytical solutions. These experimentally validated models allow for the determination of the sensor parameters for the desired performance. An augmented reality interface system for surgery skills training by optimizing sensitivities that match varying tissue stiffnesses is further demonstrated. The platform enables greater effectiveness in rapidly iterating and designing micropyramidal e‐skin for applications in augmented reality interfaces, robotics, and telehealthcare.
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