Swarm Robotics for Autonomous Aerial Robots: Features, Algorithms, Control Techniques, and Challenges

With the aim of revolutionizing various industries, the field of Swarm Robotics (SRs) continuously offers efficient solutions to complex tasks. 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 Aerial Robots (SARs). It examines the key features and characteristics of SR, its integration with swarm intelligence, and fundamental algorithms such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE). The paper also discusses various swarm control techniques, infrastructure requirements, and challenges associated with implementing SR in Aerial Robots. Additionally, the paper outlines future research directions, emphasizing the need for robust, energy-efficient, adaptive algorithms and ethical considerations in deploying autonomous Aerial robot swarms. This study aims to provide a solid foundation for researchers and practitioners, paving the way for future advancements and interdisciplinary collaboration in this promising field.