A Fingertip Force Microscope (FFM) for Micro-Scale Morphology Characterization

Texture sensing is an essential part of tactile sensing, which extracts morphology, roughness, and hardness information during object manipulation. However, biological texture sensing is only a qualitative description of object features and shows low spatial resolution. Current research on artificial tactile sensing systems mainly focuses on machine learning-based qualitative comparison of different surfaces with different roughness. Here, we present a wearable artificial fingertip consisting of two piezoelectric vibration tips for quantitative morphology characterization. Two sensing tips with fixed spacing will bend and recover while sliding the artificial fingertip over uneven surfaces. Piezoelectric films on the tips transform vibrations into voltage signals. The two-tip design enables the identification of instantaneous speed. By correlating voltage signals with the actual moving condition and the calculated instantaneous speed, the time-domain information indicates the groove width, bar width, and groove depth of the grating texture. Therefore, textures with height of 1μm~3mm and distances beyond 200 μm can be detected without the need for controlled speed and pressing force. Further, the artificial fingertip can be worn on fingers and generates micro-scale morphology information. The artificial fingertip was further integrated into a robotic hand for obtaining morphology information from multiple slides. Three-dimensional (3D) reconstruction of fine micro-scale patterns can be generated through a quick sweep in real time.