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A Comprehensive Review of Next-Gen UAV Swarm Robotics: Optimisation Techniques and Control Strategies for Dynamic Environments

by Ghulam E Mustafa Abro1,*, Ayman M Abdallah1,2, Faizan Zahid3, Saleem Ahmed4

1 Interdisciplinary Research Centre for Aviation and Space Exploration (IRC-ASE), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, 31261, Saudi Arabia
2 Aerospace Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, 31261, Saudi Arabia
3 Department of Electrical Electronics and Computer Engineering, University of Catania, Piazza Università, Catania, 95124, Italy
4 Department of Electrical Engineering, Quaid-e-Awam University of Engineering Sciences and Technology (QUEST), Nawabshah, 67480, Pakistan

* Corresponding Author: Ghulam E Mustafa Abro. Email: email

Intelligent Automation & Soft Computing 2025, 40, 99-123. https://doi.org/10.32604/iasc.2025.060364

Abstract

This review synthesises and assesses the most recent developments in Unmanned Aerial Vehicles (UAVs) and swarm robotics, with a specific emphasis on optimisation strategies, path planning, and formation control. The study identifies key methodologies that are driving progress in the field by conducting a comprehensive analysis of seven critical publications. The following are included: sensor-based platforms that facilitate effective obstacle avoidance, cluster-based hierarchical path planning for efficient navigation, and adaptive hybrid controllers for dynamic environments. The review emphasises the substantial contribution of optimisation techniques, including Max-Min Ant Colony Optimisation (MMACO), to the improvement of convergence rates and the enhancement of path efficiency. The effectiveness of various navigation systems in diverse operational contexts is demonstrated through comparative analysis, which provides valuable insights into the system’s adaptability and performance. The primary findings underscore the strengths and limitations of current methodologies, thereby identifying voids in research and practical applications. This review offers actionable insights for academicians and practitioners who are striving to advance UAV and swarm robotics technology by addressing these challenges. The study concludes with a discussion of future directions, which underscores the potential for innovative solutions to enhance UAV systems in complex, dynamic environments.

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Cite This Article

APA Style
Abro, G.E.M., Abdallah, A.M., Zahid, F., Ahmed, S. (2025). A comprehensive review of next-gen UAV swarm robotics: optimisation techniques and control strategies for dynamic environments. Intelligent Automation & Soft Computing, 40(1), 99–123. https://doi.org/10.32604/iasc.2025.060364
Vancouver Style
Abro GEM, Abdallah AM, Zahid F, Ahmed S. A comprehensive review of next-gen UAV swarm robotics: optimisation techniques and control strategies for dynamic environments. Intell Automat Soft Comput. 2025;40(1):99–123. https://doi.org/10.32604/iasc.2025.060364
IEEE Style
G. E. M. Abro, A. M. Abdallah, F. Zahid, and S. Ahmed, “A Comprehensive Review of Next-Gen UAV Swarm Robotics: Optimisation Techniques and Control Strategies for Dynamic Environments,” Intell. Automat. Soft Comput., vol. 40, no. 1, pp. 99–123, 2025. https://doi.org/10.32604/iasc.2025.060364



cc Copyright © 2025 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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