UAV swarms: research, challenges, and future directions
Yunes Alqudsi, Murat Makaracı
- Year
- 2025
- Citations
- 123
- Access
- Open access
Abstract
Abstract 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.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002