This paper presents a neuromorphic, event-driven tactile sensing system for soft, large-area skin, based on the Dynamic Vision Sensors (DVS) integrated with a flexible silicone optical waveguide skin. Instead of repetitively scanning embedded photoreceivers, this design uses a stereo vision setup comprising two DVS cameras looking sideways through the skin. Such a design produces events as changes in brightness are detected, and estimates press positions on the 2D skin surface through triangulation, utilizing Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to find the center of mass of contact events resulting from pressing actions. The system is evaluated over a 4620 mm2 probed area of the skin using a meander raster scan. Across 95 % of the presses visible to both cameras, the press localization achieved a Root-Mean-Squared Error (RMSE) of 4.66 mm. The results highlight the potential of this approach for wide-area flexible and responsive tactile sensors in soft robotics and interactive environments. Moreover, we examined how the system performs when the amount of event data is strongly reduced. Using stochastic down-sampling, the event stream was reduced to 1/1024 of its original size. Under this extreme reduction, the average localization error increased only slightly (from 4.66 mm to 9.33 mm), and the system still produced valid press localizations for 85 % of the trials. This reduction in pass rate is expected, as some presses no longer produce enough events to form a reliable cluster for triangulation. These results show that the sensing approach remains functional even with very sparse event data, which is promising for reducing power consumption and computational load in future implementations. The system exhibits a detection latency distribution with a characteristic width of 31 ms.

翻译：本文提出了一种用于大面积柔性皮肤的神经形态事件驱动触觉传感系统，该系统基于动态视觉传感器（DVS）与柔性硅胶光学波导皮肤集成。该设计并非重复扫描嵌入式光接收器，而是采用了一种立体视觉设置，包含两个从侧面透过皮肤观察的DVS摄像头。此设计在检测到亮度变化时产生事件，并通过三角测量法估计二维皮肤表面的按压位置，利用基于密度的噪声应用空间聚类（DBSCAN）算法来寻找由按压动作产生的接触事件质心。该系统在皮肤4620 mm²的探测区域内使用蛇形光栅扫描进行评估。在95%能被两个摄像头同时观测到的按压中，按压定位的均方根误差（RMSE）达到4.66 mm。结果凸显了该方法在软体机器人和交互环境中实现大面积柔性响应式触觉传感器的潜力。此外，我们研究了在事件数据量大幅减少时系统的性能表现。通过随机下采样，事件流被缩减至原始大小的1/1024。在此极端缩减条件下，平均定位误差仅略有增加（从4.66 mm增至9.33 mm），系统仍能在85%的试验中产生有效的按压定位。通过率的下降是预期的，因为部分按压不再产生足够的事件以形成可靠的三角测量聚类。这些结果表明，即使在事件数据极其稀疏的情况下，该传感方法仍能保持功能，这对于降低未来实现的功耗和计算负载具有积极前景。系统的检测延迟分布特征宽度为31 ms。