Towards Artificial Nerves: Biomimetic Optical-Fiber Tactile Sensing for Robots
Robotics
Summary
The authors developed OptiTac, a new robotic skin that mimics how human touch sensors work by linking tiny pins to optical fibers acting like nerves. This setup sends touch information away from the surface without losing detail, making it easier to spread sensors across a robot. Instead of complex AI, the authors use simple image-like methods to figure out where and how something is touching the sensor. Their approach shows how ideas from biology can help robots sense touch more naturally and clearly.
Authors
Laura E. Butcher, Chris J. Ford, Nathan F. Lepora, Efi Psomopoulou
Abstract
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.