Path Planning Research of a UAV Base Station Searching for Disaster Victims’ Location Information Based on Deep Reinforcement Learning

Path Planning Research of a UAV Base Station Searching for Disaster Victims’ Location Information Based on Deep Reinforcement Learning

Aiming at the path planning problem of unmanned aerial vehicle (UAV) base stations when performing search tasks, this paper proposes a Double DQN-state splitting Q network (DDQN-SSQN) algorithm that combines state splitting and optimal state to complete the optimal path planning of UAV based on the...

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Bibliografiska uppgifter
Huvudupphovsmän: Jinduo Zhao, Zhigao Gan, Jiakai Liang, Chao Wang, Keqiang Yue, Wenjun Li, Yilin Li, Ruixue Li
Materialtyp: Artikel
Språk:English
Publicerad: MDPI AG 2022-12-01
Serie:Entropy
Ämnen:
UAV base station
path planning
deep reinforcement learning
received signal strength
Länkar:https://www.mdpi.com/1099-4300/24/12/1767

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https://www.mdpi.com/1099-4300/24/12/1767

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