Abstract
Drones operating in complex environments face a significant threat from thin obstacles, such as steel wires and kite strings at the submillimeter level, which are notoriously difficult for conventional sensors like RGB cameras, LiDAR, and depth cameras to detect. This paper introduces SkyShield, an event-driven, end-to-end framework designed for the perception of submillimeter scale obstacles. Drawing upon the unique features that thin obstacles present in the event stream, our method employs a lightweight U-Net architecture and an innovative Dice-Contour Regularization Loss to ensure precise detection. Experimental results demonstrate that our event-based approach achieves mean F1 Score of 0.7088 with a low latency of 21.2 ms, making it ideal for deployment on edge and mobile platforms.
Abstract (translated)
在复杂环境中运行的无人机面临着来自细小障碍物（如钢丝和风筝线）的重大威胁，这些障碍物通常小于毫米级，对于传统的传感器来说非常难以检测，比如RGB相机、激光雷达和深度摄像头。本文介绍了SkyShield，这是一种基于事件驱动、端到端设计的框架，专门用于感知毫米以下级别的障碍物。通过利用细小障碍物在事件流中呈现的独特特征，我们的方法采用了轻量级U-Net架构，并创新性地引入了Dice轮廓正则化损失，以确保精确检测。 实验结果显示，基于事件的方法实现了0.7088的平均F1分数和21.2毫秒的低延迟，使其非常适合部署在边缘计算和移动平台上。
URL
https://arxiv.org/abs/2508.09397
