An analysis of the robustness of UAV agriculture field coverage using multi-agent reinforcement learning-Reference-Cited by-同舟云学术

An analysis of the robustness of UAV agriculture field coverage using multi-agent reinforcement learning

Published:2023-04 Issue:4 Volume:15 Page:2317-2327
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Marwah Nirmal,Singh Vivek Kumar,Kashyap Gautam Siddharth^ORCID,Wazir Samar

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-023-01264-0.pdf

Reference40 articles.

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3. Selma B, Chouraqui S, Abouaïssa H (2020) “Optimal trajectory tracking control of unmanned aerial vehicle using ANFIS-IPSO system,” Int. J. Inf. Technol, vol. 12, no. 2, pp. 383–395, Jun. doi: https://doi.org/10.1007/s41870-020-00436-6

4. Mahbub M (2021) Unmanned aerial vehicle-collaborative 5G: a cooperative technology for enhancement of 5G NR. Int J Inf Technol 13(2):793–799. https://doi.org/10.1007/s41870-021-00623-z

5. Yasin JN, Mohamed SAS, Haghbayan MH, Heikkonen J, Tenhunen H, Plosila J (2021) Low-cost ultrasonic based object detection and collision avoidance method for autonomous robots. Int J Inf Technol 13(1):97–107. https://doi.org/10.1007/s41870-020-00513-w

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