Obstacle avoidance in unmanned aerial vehicles using image segmentation and deep learning
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Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Machine learning is a branch of artificial intelligence based on the idea that systems can learn to identify patterns and make decisions with a minimum of human intervention. In this study, demonstration learning will be used, using neural networks in a prototype of a drone built to perform trajectories in controlled environments. To accelerate the training convergence process, a new training data selection approach has been introduced, which picks data from the experience pool based on priority instead of randomness. An autonomous maneuver strategy for dual-UAV olive formation air warfare is provided, which makes use of UAV capabilities such as obstacle avoidance, formation, and confrontation to maximize the effectiveness of the attack.
Açıklama
Anahtar Kelimeler
LEACH, PSO, Routing, WSN
Kaynak
ISMSIT 2022 - 6th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Obaid, A. A., Koyuncu, H. (2022). Obstacle avoidance in unmanned aerial vehicles using image segmentation and deep learning. In 2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 912-915). IEEE.
