Tactile sensing represents a crucial technique that can enhance the performance of robotic manipulators in various tasks. This work presents a novel bioinspired neuromorphic vision-based tactile sensor that uses an event-based camera to quickly capture and convey information about the interactions between robotic manipulators and their environment. The camera in the sensor observes the deformation of a flexible skin manufactured from a cheap and accessible 3D printed material, whereas a 3D printed rigid casing houses the components of the sensor together. The sensor is tested in a grasping stage classification task involving several objects using a data-driven learning-based approach. The results show that the proposed approach enables the sensor to detect pressing and slip incidents within a speed of 2 ms. The fast tactile perception properties of the proposed sensor makes it an ideal candidate for safe grasping of different objects in industries that involve high-speed pick-and-place operations.

翻译：触觉感知是一项关键技术，可提升机器人操作器在各种任务中的性能。本文提出一种新型生物启发式神经形态视觉触觉传感器，该传感器采用事件相机快速捕获并传递机器人操作器与环境交互的信息。传感器内部的相机负责观测由廉价易得的3D打印材料制成的柔性蒙皮形变，而3D打印的刚性外壳则用于封装传感器各组件。通过数据驱动的学习方法，在涉及多种物体的抓取阶段分类任务中对该传感器进行测试。结果表明，所提方法使传感器能在2毫秒内检测到按压和滑移事件。该传感器具备快速触觉感知特性，使其成为高速拾放作业行业中实现不同物体安全抓取的理想选择。