迈向人造神经：用于机器人的仿生光纤触觉传感
Towards Artificial Nerves: Biomimetic Optical-Fiber Tactile Sensing for Robots
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中文总结 AI 辅助
研究旨在为机器人开发仿生光纤触觉传感，以实现类人触觉感知。核心方法是OptiTac传感器模拟人类触觉结构，将触觉信号当图像用简单分析方法处理。主要贡献是建立传感框架，为未来分布式触觉系统提供可扩展路线，展示生物学原理对机器人人工神经开发的指导作用。
中文摘要 AI 辅助
机器人系统越来越需要接近人类皮肤适应性和分辨率的触觉传感，以实现灵巧操作和安全交互。OptiTac是一种仿生触觉传感器，通过将柔软皮肤上的每个机械引脚与充当人造神经的光纤配对，模拟人类触觉的机械感受器到神经的结构。该设计展示了一种在保持高空间分辨率的同时将触觉信息从传感表面路由出去的架构原理。通过将触觉信号视为图像，使用简单的分析方法而非不透明的深度学习模型来推断接触位置、大小和形状，提供可解释和可扩展的触觉智能。这项工作展示了生物学中的进化原理如何指导机器人人工神经系统的开发，为下一代机器人平台实现类人触觉感知提供了一条途径。更广泛地说，OptiTac建立了一个用于可解释机器人触觉的人造神经启发的传感框架和一条通往未来分布式触觉系统的可扩展路线。
英文摘要
Robotic systems increasingly demand tactile sensing that approaches the adaptability and resolution of human skin to enable dexterous manipulation and safe interaction. OptiTac is a biomimetic tactile sensor that emulates the mechanoreceptor-to-nerve architecture of human touch by pairing each mechanical pin on a soft skin with an optical fiber acting as an artificial nerve. This design demonstrates an architectural principle for routing tactile information away from the sensing surface while preserving high spatial resolution, establishing a practical route toward distributed tactile sensing in future robotic systems. By treating tactile signals as images, simple analytical methods, rather than opaque deep-learning models, are used to infer contact location, size, and shape, providing interpretable and scalable tactile intelligence. This work demonstrates how evolutionary principles from biology can guide the development of artificial nerve systems for robots, offering a pathway toward human-like tactile perception in next-generation robotic platforms. More broadly, OptiTac establishes an artificial nerve-inspired sensing framework for interpretable robotic touch and a scalable route toward future distributed tactile systems.
发表机构
- School of Engineering Mathematics and Technology, University of Bristol（工程数学与技术学院，布里斯托大学）
机构由 AI 辅助整理，请以论文原文为准。
