Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin
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DOI：
10.1038/s42256-022-00487-3
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发表时间：
2022-05-01
影响因子：
23.8
通讯作者：
Oddo, Calogero Maria
中科院分区：
文献类型：
--
作者：
Massari, Luca;Fransvea, Giulia;Oddo, Calogero Maria
机器人需要触觉传感才能在日常生活和工作场所与人类进行物理交互。机器人技术的一个科学挑战是如何同时检测接触位置和强度。作者描述了一种用于机器人系统应用的大面积传感皮肤，特别是用于人机交互。协作机器人有望在日常生活和工作场所（包括工业和医疗保健环境）中与人类进行物理交互。一项关键的相关使能技术是触觉传感，目前需要解决突出的科学挑战，通过柔软舒适的人造皮肤来同时检测接触位置和强度，该人造皮肤大面积适应机器人实施例的复杂弯曲几何形状。在这项工作中，提出了具有弯曲几何形状的大面积敏感软皮肤的开发，允许通过模块化贴片覆盖机器人全身。仿生皮肤由柔软的聚合物基质组成，类似于人类前臂，嵌入光子光纤布拉格光栅传感器，部分模仿鲁菲尼机械感受器功能，具有扩散、重叠的感受野。采用卷积神经网络深度学习算法和多重网格神经元集成过程来解码光纤布拉格光栅传感器输出，以推断接触力大小和通过皮肤表面的定位。力和定位预测的中值误差分别为 35 mN（四分位距 56 mN）和 3.2 mm（四分位距 2.3 mm）。拟人化手臂的演示为基于人工智能的集成皮肤铺平了道路，通过机器智能实现安全的人机合作。
Tactile sensing is needed for robots to physically interact with humans in daily living and in the workplace. A scientific challenge in robotics is how to simultaneously detect contact location and intensity. The authors describe a large-area sensing skin for robotic system applications, specifically for human-machine interactions.Collaborative robots are expected to physically interact with humans in daily living and the workplace, including industrial and healthcare settings. A key related enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic fibre Bragg grating transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A convolutional neural network deep learning algorithm and a multigrid neuron integration process were implemented to decode the fibre Bragg grating sensor outputs for inference of contact force magnitude and localization through the skin surface. Results of 35 mN (interquartile range 56 mN) and 3.2 mm (interquartile range 2.3 mm) median errors were achieved for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards artificial intelligence based integrated skins enabling safe human-robot cooperation via machine intelligence.