An Efficient Sampling-Based Algorithms Using Active Learning and Manifold Learning for Multiple Unmanned Aerial Vehicle Task Allocation under Uncertainty

This paper presents a sampling-based approximation for multiple unmanned aerial vehicle (UAV) task allocation under uncertainty. Our goal is to reduce the amount of calculations and improve the accuracy of the algorithm. For this purpose, Gaussian process regression models are constructed from an un...

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Vydané v:	Sensors (Basel, Switzerland) Ročník 18; číslo 8; s. 2645
Hlavní autori:	Fu, Xiaowei, Wang, Hui, Li, Bin, Gao, Xiaoguang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 12.08.2018 MDPI
Predmet:	Active learning manifold learning multi-UAVs task allocation Teaching methods uncertainty Unmanned aerial vehicles multi-UAVs task allocation active learning uncertainty manifold learning
ISSN:	1424-8220, 1424-8220
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