Perception systems for ornithopters face severe challenges. The harsh vibrations and abrupt movements caused during flapping are prone to produce motion blur and strong lighting condition changes. Their strict restrictions in weight, size, and energy consumption also limit the type and number of sensors to mount onboard. Lightweight traditional cameras have become a standard off-the-shelf solution in many flapping-wing designs. However, bioinspired event cameras are a promising solution for ornithopter perception due to their microsecond temporal resolution, high dynamic range, and low power consumption. This paper presents an experimental comparison between frame-based and an event-based camera. Both technologies are analyzed considering the particular flapping-wing robot specifications and also experimentally analyzing the performance of well-known vision algorithms with data recorded onboard a flapping-wing robot. Our results suggest event cameras as the most suitable sensors for ornithopters. Nevertheless, they also evidence the open challenges for event-based vision on board flapping-wing robots.

翻译：扑翼飞行器（ornithopter）的感知系统面临严峻挑战。扑翼运动过程中产生的剧烈振动与突发动作易引发运动模糊及光照条件剧变，而其对重量、尺寸及能耗的严格限制也约束了可搭载传感器的类型与数量。轻型传统相机已成为多数扑翼设计的标准商用解决方案。然而，受生物启发的基于事件的相机凭借微秒级时间分辨率、高动态范围与低功耗特性，成为扑翼飞行器感知领域的潜力方案。本文通过实验对比了基于帧的相机与基于事件的相机：结合扑翼机器人特定规格分析两项技术特性，并基于扑翼机器人机载记录数据，实验评估了经典视觉算法的性能表现。研究结果表明，基于事件的相机是最适配扑翼飞行器的传感器，但同时也揭示了扑翼机器人机载事件视觉面临的开放性挑战。