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Persistent Charging System for Crazyflie Platform
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AI
DOI：10.3390/drones6080212.png)
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Nowadays, quadcopters are used widely in different applications, but their flight time is limited during operation. In this paper, a precision landing method based on a Kalman filter is proposed for an autonomous indoor persistent drone system that aims to increase the flight time of quadcopters. First, a local positioning system is used for tracking performance. Second, instead of using this local positioning system during the landing phase, a multi-ranger sensor is proposed to increase the accuracy of horizontal errors. Next, based on the relative position provided by the multi-ranger sensor, a Kalman filter technique is applied to estimate the relative velocity of the system, which is then applied to control the position of the quadcopter during the landing phase. Finally, a charging state machine law is proposed to charge the battery of three quadcopters sequentially. The experimental results demonstrate that the proposed concept based on a multi-ranger sensor can enhance the accuracy of the landing phase in comparison with the conventional method.
Keyword:
wireless charging
quadcopter
unmanned aerial vehicle (UAV)
precision landing
期刊
D
IF:
4.8
论文数:
3.9K
被引数:
8.3K
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引用论文
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