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

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.