Optimizing Multi-Follower Formation in Leader-Follower Strategies for UAV Swarms

The unmanned aircraft vehicle named shortly (UAV) functions akin to a programmed human brain, serving as a tool discovered by humans to overcome various challenges in life. As it excelled in its assigned tasks, researchers and developers began exploring the potential of utilizing swarms of UAVs to accomplish multiple tasks or even sub-tasks within a larger objective. To harness the benefits of these capabilities exhibited by UAV flocks, researchers devised different control strategies that focused on optimizing the distribution of swarm agents for optimal performance. Among these strategies, the leader-follower approach emerged as one of the most prominent and significant methods for distributing UAV flocks, which researchers have applied across various scenarios. In the present study, the objective is to investigate the optimal of the follower's position and distribution relative to the leader according the swarm's task. The researchers conducted a comparison of two distribution patterns and employed MATLAB to test the swarm's ability to navigate around static obstacles. The final results demonstrated that adopting a distribution pattern resembling the Diamond Formation “Triangle and M-shape distribution” with the leader yielded the best and least erroneous outcomes. Conversely, the Follower Formation “Linear Distribution” exhibited the poorest performance and the highest number of errors.