In the last decade, UAVs have become a widely used technology. As they are used by both professionals and amateurs, there is a need to explore different control modalities to make control intuitive and easier, especially for new users. In this work, we compared the most widely used joystick control with a custom human pose control. We used human pose estimation and arm movements to send UAV commands in the same way that operators use their fingers to send joystick commands. Experiments were conducted in a simulation environment with first-person visual feedback. Participants had to traverse the same maze with joystick and human pose control. Participants' subjective experience was assessed using the raw NASA Task Load Index.

翻译：过去十年间，无人机已成为广泛应用的技术。由于操作者涵盖专业人士与业余爱好者，探索不同控制模式以实现直观简易的操作（尤其对新用户而言）显得尤为必要。本研究将最常用的摇杆控制与定制化人体姿态控制进行了对比。通过人体姿态估计与手臂动作，我们实现了与操作者用手指发送摇杆指令相同方式的无人机指令传输。实验在配备第一人称视觉反馈的仿真环境中进行，参与者需分别使用摇杆与人体姿态控制穿越相同迷宫。采用原始NASA任务负荷指数评估了参与者的主观体验。