Autonomous flight of flapping-wing robots is a major challenge for robot perception. Most of the previous sense-and-avoid works have studied the problem of obstacle avoidance for flapping-wing robots considering only static obstacles. This paper presents a fully onboard dynamic sense-and-avoid scheme for large-scale ornithopters using event cameras. These sensors trigger pixel information due to changes of illumination in the scene such as those produced by dynamic objects. The method performs event-by-event processing in low-cost hardware such as those onboard small aerial vehicles. The proposed scheme detects obstacles and evaluates possible collisions with the robot body. The onboard controller actuates over the horizontal and vertical tail deflections to execute the avoidance maneuver. The scheme is validated in both indoor and outdoor scenarios using obstacles of different shapes and sizes. To the best of the authors' knowledge, this is the first event-based method for dynamic obstacle avoidance in a flapping-wing robot.

翻译：扑翼机器人的自主飞行是机器人感知领域的一项重大挑战。以往大多数关于避撞的研究仅考虑了静态障碍物下的扑翼机器人避障问题。本文提出了一种完全机载的、基于事件相机的动态感知与避撞方案，适用于大型扑翼机器人。这类传感器通过场景中（如动态物体产生的）光照变化触发像素信息。该方法在低成本硬件（如小型飞行器机载设备）上实现逐事件处理。所提方案可检测障碍物并评估与机器人本体的潜在碰撞风险。机载控制器通过驱动水平与垂直尾翼偏转执行避撞机动。该方案在室内外场景中利用不同形状与尺寸的障碍物进行了验证。据作者所知，这是首次在扑翼机器人上基于事件方法实现动态障碍物避让。