Skin‐Inspired Multi‐Modal Mechanoreceptors for Dynamic Haptic Exploration

Abstract

Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in our skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanism. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, we develop a skin‐inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli to bridge sensing and action in a closed‐loop sensorimotor system for dynamic haptic exploration. A tensor‐based non‐linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, we further demonstrate a closed‐loop robotic system capable of recognizing objects with improved accuracy (∼96%). This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep‐sea exploration.This article is protected by copyright. All rights reserved

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“…A tactile sensor comprising four sensitive strain gauges (sensor #1, #2, #3, and #4) was designed and fabricated that could differentiate normal and shear force. In our previous publication, an analytical and numerical modal to guide the design of tactile sensor was introduced ( Su et al, 2024 ). This is a universal strategy to design and fabricate tactile sensors that can differentiate normal and shear forces and similar mechanisms to detect normal and shear forces have also been reported by ( Harada et al, 2014 ; Won et al, 2019 ; Gao et al, 2023 ).…”

“…Flexible printed circuits were used to connect the sensor to a data acquisition platform (Arduino). Extensive experimentation details along with a step-wise fabrication process have been provided in a previous work ( Su et al, 2024 ).…”