Unmanned Aerial Vehicle (UAV) swarms represent a transformative advancement in aerial robotics, leveraging collaborative autonomy to enhance operational capabilities. This paper provides a comprehensive exploration of UAV swarm infrastructure, recent research advancements, and diverse applications. Key areas such as coordinated path planning, task assignment, formation control, and security considerations are examined, highlighting how Artificial Intelligence (AI) and Machine Learning (ML) are integrated to improve decision-making and adaptability. Applications span civilian sectors, including entertainment, infrastructure inspection, and delivery services, as well as military applications in surveillance, combat support, and logistics. The paper addresses technical challenges, regulatory constraints, and ethical considerations, while outlining future directions focused on scalability, robustness, and societal integration. This review consolidates the evolving landscape of UAV swarms, identifying critical challenges and guiding future research endeavors.

Swarm Robotics (SR) is an interdisciplinary field that is rapidly advancing to address complex industrial challenges. This paper provides a comprehensive review of recent advancements and emerging trends in SR, with a specific focus on the coordination and control of Swarm Flying Robots (SFRs). The motivation behind this review is to explore scalable and robust solutions for SFRs to enhance their performance and adaptability across various applications. Key objectives include examining the characteristics and essential behaviors of SR, analyzing the challenges and so lutions for implementing SR in Flying Robots (FRs), and highlighting current and future research directions. The review delves into critical areas such as multiple robot path planning, Swarm Intelligence (SI), combinatorial optimization, and formation flying using SFR. Special attention is given to coordination and control techniques, including formation control in GPS-denied environments, to underscore their significance in advancing SR. The paper also addresses ethical, privacy, and security considerations, emphasizing the importance of responsible practices in SR development. Major takeaways from this review include the identification of key technical challenges and potential solutions in SFR, the exploration of SI algorithms, and the future research directions necessary for fully realizing the potential of SR technologies. By offering detailed insights into state-of-the-art research and its industrial implications, this paper serves as a foundational guide for future studies in the dynamic and promising domain of swarm robotics.

The rapid development of Unmanned Aerial Vehicles (UAVs) leads to expand the application of such technologies in various fields. The detection and mapping of landmines are one of the challenging and critical areas. The provision of efficient airborne detection technologies will save the lives of thousands of civilians and even workers involved in such dangerous missions. The objective of this paper is to provide a brief review of the state-of-the-art airborne landmine detection studies for researchers to further explore. We have also proposed a promising direction for future research towards a reliable, efficient, and integrated UAV-based landmine detection system.