Flapping‐Wing Dynamics as a Natural Detector of Wind Direction

Kazutoshi Tanaka, Shihao Yang, Yuji Tokudome, Yuna Minami, Yuyao Lu, T. Arie, S. Akita, K. Takei, K. Nakajima
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引用次数: 10

Abstract

Flapping‐wing unmanned aerial vehicles have potential advantages, such as consuming lower energy by leveraging the force of wind. Since the flapping movements of the soft wings contain information about the wind, measuring the movement of each part of the wings allows these vehicles to distinguish the direction of the wind. To confirm this prediction, herein, the detection of wind flow from the flapping‐wing motion of a bird robot using an integrated flexible strain sensor on its wing and a physical reservoir computing analysis is presented. In the presence of different wind directions, the movement of the flapping‐wings is measured using flexible strain sensors, and the current wind direction is detected by capitalizing on the intrinsic wing dynamics. As a result, it is found that the detection accuracy using our embedded flexible strain sensors is significantly high, showing a similar level of accuracy with a high‐speed camera recorded from the fixed position in the environment. The results indicate that flapping‐wing unmanned aerial vehicles can recognize wind direction by exploiting the natural dynamics of their wings.
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扑翼动力学作为风向的自然探测器
扑翼无人机具有潜在的优势,例如通过利用风力消耗更低的能量。由于软翼的拍打运动包含了风的信息,因此测量机翼各部分的运动可以让这些飞行器区分风的方向。为了证实这一预测,本文提出了利用机翼上的集成柔性应变传感器和物理储层计算分析来检测鸟类机器人扑翼运动中的气流。在不同风向下,扑翼的运动是用柔性应变传感器测量的,当前风向是利用机翼的固有动力学来检测的。结果发现,使用我们的嵌入式柔性应变传感器的检测精度非常高,显示出与高速摄像机从环境中的固定位置记录的精度相似的水平。结果表明,扑翼无人机可以利用机翼的自然动力学特性来识别风向。
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