Touch is a crucial sensing modality that provides rich information about object properties and interactions with the physical environment. Humans and robots both benefit from using touch to perceive and interact with the surrounding environment (Johansson and Flanagan, 2009; Li et al., 2020; Calandra et al., 2017). However, no existing systems provide rich, multi-modal digital touch-sensing capabilities through a hemispherical compliant embodiment. Here, we describe several conceptual and technological innovations to improve the digitization of touch. These advances are embodied in an artificial finger-shaped sensor with advanced sensing capabilities. Significantly, this fingertip contains high-resolution sensors (~8.3 million taxels) that respond to omnidirectional touch, capture multi-modal signals, and use on-device artificial intelligence to process the data in real time. Evaluations show that the artificial fingertip can resolve spatial features as small as 7 um, sense normal and shear forces with a resolution of 1.01 mN and 1.27 mN, respectively, perceive vibrations up to 10 kHz, sense heat, and even sense odor. Furthermore, it embeds an on-device AI neural network accelerator that acts as a peripheral nervous system on a robot and mimics the reflex arc found in humans. These results demonstrate the possibility of digitizing touch with superhuman performance. The implications are profound, and we anticipate potential applications in robotics (industrial, medical, agricultural, and consumer-level), virtual reality and telepresence, prosthetics, and e-commerce. Toward digitizing touch at scale, we open-source a modular platform to facilitate future research on the nature of touch.

翻译：触觉是一种关键的感知模态，能够提供关于物体属性及其与物理环境交互的丰富信息。人类和机器人均可通过触觉来感知周围环境并与之互动，从而获益（Johansson and Flanagan, 2009; Li et al., 2020; Calandra et al., 2017）。然而，目前尚无任何现有系统能够通过半球形柔顺实体提供丰富的多模态数字触觉感知能力。本文阐述了几项旨在改进触觉数字化的概念与技术革新。这些进展体现在一个具备先进感知能力的人工指形传感器中。尤为重要的是，该指尖集成了高分辨率传感器（约830万个触觉单元），能够响应全向触觉、捕获多模态信号，并利用设备端人工智能实时处理数据。评估结果表明，该人工指尖能够分辨小至7微米的空间特征，分别以1.01 mN和1.27 mN的分辨率感知法向力与剪切力，检测高达10 kHz的振动，感知热量，甚至能感知气味。此外，它还嵌入了设备端AI神经网络加速器，作为机器人的外周神经系统，模拟了人类的条件反射弧。这些结果证明了实现超越人类性能的触觉数字化的可能性。其影响深远，我们预期该技术将在机器人（工业、医疗、农业及消费级）、虚拟现实与远程呈现、假肢以及电子商务等领域具有潜在应用前景。为实现大规模触觉数字化，我们开源了一个模块化平台，以促进未来关于触觉本质的研究。