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arXiv · 1705.10375

Indoor UAV Navigation to a Rayleigh Fading Source Using Q-Learning

Bekir Sait Ciftler·Adem Tuncer·Ismail Guvenc
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Abstract

Unmanned aerial vehicles (UAVs) can be used to localize victims, deliver first-aid, and maintain wireless connectivity to victims and first responders during search/rescue and public safety scenarios. In this letter, we consider the problem of navigating a UAV to a Rayleigh fading wireless signal source, e.g. the Internet-of-Things (IoT) devices such as smart watches and other wearables owned by the victim in an indoor environment. The source is assumed to transmit RF signals, and a Q-learning algorithm is used to navigate the UAV to the vicinity of the source. Our results show that the time averaging window and the exploration rate for the Q-learning algorithm can be optimized for fastest navigation of the UAV to the IoT device. As a result, Q-learning achieves the best performance with smaller convergence time overall.

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Bekir Sait Ciftler, Adem Tuncer, Ismail Guvenc. 2017-05-29. Indoor UAV Navigation to a Rayleigh Fading Source Using Q-Learning. https://arxiv.org/abs/1705.10375

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