The drone industry is diversifying and the number of pilots increases rapidly. In this context, flight schools need adapted tools to train pilots, most importantly with regard to their own awareness of their physiological and cognitive limits. In civil and military aviation, pilots can train themselves on realistic simulators to tune their reaction and reflexes, but also to gather data on their piloting behavior and physiological states. It helps them to improve their performances. Opposed to cockpit scenarios, drone teleoperation is conducted outdoor in the field, thus with only limited potential from desktop simulation training. This work aims to provide a solution to gather pilots behavior out in the field and help them increase their performance. We combined advance object detection from a frontal camera to gaze and heart-rate variability measurements. We observed pilots and analyze their behavior over three flight challenges. We believe this tool can support pilots both in their training and in their regular flight tasks. A demonstration video is available on https://www.youtube.com/watch?v=eePhjd2qNiI
翻译:无人驾驶飞机的行业正在多样化,飞行员的数量正在迅速增加。在这方面,飞行学校需要经调整的工具来培训飞行员,最重要的是他们自己对生理和认知限制的认识。在民用和军用航空中,飞行员可以对现实的模拟器进行训练,以调和反应和反射,同时也可以收集其实验行为和生理状态的数据。这帮助他们改进他们的表演。反对驾驶舱的情景,无人驾驶远程操作在外地室外进行,因此桌面模拟培训的潜力有限。这项工作旨在提供一种解决方案,以收集飞行员在外地的行为,帮助他们提高性能。我们从前视镜头和心率变异测量中结合了前方物体探测,我们观察了三个飞行挑战并分析了它们的行为。我们认为,这一工具可以支持飞行员的训练及其常规飞行任务。一个演示视频可在https://www.youtube.com/watch?v=eePhjd2qNii上查阅。