Formation control plays a vital role in coordinating multi-agent systems and swarm robotics, enabling collaboration in applications such as autonomous vehicles, robotic swarms, and distributed sensing. This paper introduces the formation-control problem, highlights its challenges, and compares centralized and decentralized schemes. We review recent advances and analyze popular algorithms, then propose a hybrid framework that combines leader–follower tracking with an artificial potential field (APF) safety layer. In three-UAV tests, the followers cross paths and one encounters a static obstacle. We run multiple simulations across scenarios with obstacles and varying formations. Results show the hybrid controller maintains the required formation while avoiding inter-agent collisions. Using quantitative metrics, we find the leader–follower baseline achieves the lowest formation error but has the most safety violations, whereas APF greatly improves safety at the cost of higher error. The hybrid combines these strengths—delivering APF-level safety with lower error and negligible runtime overhead—providing a practical balance between precise formation keeping and robust collision avoidance.