Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2024, Cilt: 8 Sayı: 2, 81 - 85

Öz

Kaynakça

  • [1] Shao, Y., & Yang, S. (2020). Applications of Generative Adversarial Networks (GANs) in Aircraft Design: A Survey. Aerospace, 7(8), 108. https://doi.org/10.3390/aerospace7080108
  • [2] Zhou, D., Hu, H., Wu, J., & Peng, Z. (2020). Generative adversarial networks in UAV-aided communications: A comprehensive survey. IEEE Access, 8, 135857-135876. https://doi.org/10.1109/ACCESS.2020.3015019
  • [3] Karaman, S., & Frazzoli, E. (2020). Autonomous aerial vehicles: A survey of the state of the art. Proceedings of the IEEE, 108(2), 252-294. https://doi.org/10.1109/JPROC.2019.2955685
  • [4] Brown, C., De Wet, P., Bruckstein, A. M., & Sukkarieh, S. (2020). A survey of visual SLAM in unmanned aerial vehicles. Journal of Field Robotics, 37(3), 405-448. https://doi.org/10.1002/rob.21892
  • [5] Khalifa, S., Mustafa, M., & Guizani, M. (2021). Machine Learning-Driven Autonomous UAV Navigation: Challenges and Opportunities. IEEE Access, 9, 73138-73156. https://doi.org/10.1109/ACCESS.2021.3073353
  • [6] Yang, L., Cui, W., & Meng, X. (2021). A Survey of Key Technologies for Autonomous Flight of UAVs. IEEE Access, 9, 68745-68766. https://doi.org/10.1109/ACCESS.2021.3070011
  • [7] Zhang, Y., Chen, L., & Zhang, H. (2020). A survey on deep learning for UAV-based communication networks. IEEE Access, 8, 22147-22159. https://doi.org/10.1109/ACCESS.2020.2960668
  • [8] Sun, Y., Yu, L., & Zhang, Y. (2021). A Survey of Machine Learning for Unmanned Aerial Vehicles: Recent Advances, Taxonomy, and Challenges. IEEE Transactions on Intelligent Transportation Systems, 22(1), 543-562. https://doi.org/10.1109/TITS.2020.2979192
  • [9] Roldán-Álvarez, D., Del-Blanco, C. R., & Cuadra-Troncoso, A. (2020). UAV-based data collection, processing, and analysis for smart agriculture: A comprehensive review of advances and applications. Computers and Electronics in Agriculture, 178, 105766. https://doi.org/10.1016/j.compag.2020.105766
  • [10] Jia, F., Dong, Y., Shi, H., Wang, J., & Chen, L. (2021). Recent advances in machine learning for unmanned aerial vehicles: Algorithms, tools, and applications. Journal of Aerospace Information Systems, 18(1), 32-49. https://doi.org/10.2514/1.I010984

Autonomous Flight Systems and Generative AI

Yıl 2024, Cilt: 8 Sayı: 2, 81 - 85

Öz

Autonomous flight systems have emerged as a significant area of research and development within the aviation industry. With the advancements in artificial intelligence (AI), particularly generative AI, these systems have witnessed substantial improvements in their capabilities and efficiency. This abstract explores the integration of generative AI techniques in autonomous flight systems and its implications on the aviation sector. Generative AI algorithms play a crucial role in various aspects of autonomous flight, including flight path planning, obstacle detection and avoidance, decision-making processes, and even aircraft design optimization. By leveraging generative AI, autonomous flight systems can adapt and respond to dynamic environments in real-time, enhancing safety, efficiency, and reliability. Furthermore, generative AI enables the generation of innovative solutions and designs that may not be apparent through traditional methods, leading to more optimized and efficient aircraft configurations. This abstract also discusses the challenges and future directions in the utilization of generative AI in autonomous flight systems, including regulatory considerations, ethical concerns, and the need for continued research and development. Overall, the integration of generative AI in autonomous flight systems represents a promising avenue for advancing the capabilities and effectiveness of aviation technology in the 21st century.

Destekleyen Kurum

Aselsan-Bites

Kaynakça

  • [1] Shao, Y., & Yang, S. (2020). Applications of Generative Adversarial Networks (GANs) in Aircraft Design: A Survey. Aerospace, 7(8), 108. https://doi.org/10.3390/aerospace7080108
  • [2] Zhou, D., Hu, H., Wu, J., & Peng, Z. (2020). Generative adversarial networks in UAV-aided communications: A comprehensive survey. IEEE Access, 8, 135857-135876. https://doi.org/10.1109/ACCESS.2020.3015019
  • [3] Karaman, S., & Frazzoli, E. (2020). Autonomous aerial vehicles: A survey of the state of the art. Proceedings of the IEEE, 108(2), 252-294. https://doi.org/10.1109/JPROC.2019.2955685
  • [4] Brown, C., De Wet, P., Bruckstein, A. M., & Sukkarieh, S. (2020). A survey of visual SLAM in unmanned aerial vehicles. Journal of Field Robotics, 37(3), 405-448. https://doi.org/10.1002/rob.21892
  • [5] Khalifa, S., Mustafa, M., & Guizani, M. (2021). Machine Learning-Driven Autonomous UAV Navigation: Challenges and Opportunities. IEEE Access, 9, 73138-73156. https://doi.org/10.1109/ACCESS.2021.3073353
  • [6] Yang, L., Cui, W., & Meng, X. (2021). A Survey of Key Technologies for Autonomous Flight of UAVs. IEEE Access, 9, 68745-68766. https://doi.org/10.1109/ACCESS.2021.3070011
  • [7] Zhang, Y., Chen, L., & Zhang, H. (2020). A survey on deep learning for UAV-based communication networks. IEEE Access, 8, 22147-22159. https://doi.org/10.1109/ACCESS.2020.2960668
  • [8] Sun, Y., Yu, L., & Zhang, Y. (2021). A Survey of Machine Learning for Unmanned Aerial Vehicles: Recent Advances, Taxonomy, and Challenges. IEEE Transactions on Intelligent Transportation Systems, 22(1), 543-562. https://doi.org/10.1109/TITS.2020.2979192
  • [9] Roldán-Álvarez, D., Del-Blanco, C. R., & Cuadra-Troncoso, A. (2020). UAV-based data collection, processing, and analysis for smart agriculture: A comprehensive review of advances and applications. Computers and Electronics in Agriculture, 178, 105766. https://doi.org/10.1016/j.compag.2020.105766
  • [10] Jia, F., Dong, Y., Shi, H., Wang, J., & Chen, L. (2021). Recent advances in machine learning for unmanned aerial vehicles: Algorithms, tools, and applications. Journal of Aerospace Information Systems, 18(1), 32-49. https://doi.org/10.2514/1.I010984
Toplam 10 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka (Diğer)
Bölüm Makaleler
Yazarlar

Ali Berkol 0000-0003-1704-1581

İdil Gökçe Demirtaş Bu kişi benim 0009-0000-4614-5211

Erken Görünüm Tarihi 11 Aralık 2024
Yayımlanma Tarihi
Gönderilme Tarihi 11 Kasım 2024
Kabul Tarihi 9 Aralık 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 8 Sayı: 2

Kaynak Göster

IEEE A. Berkol ve İ. G. Demirtaş, “Autonomous Flight Systems and Generative AI”, IJMSIT, c. 8, sy. 2, ss. 81–85, 2024.