Formation Planning with Multi-Agent Trajectory Prediction

Unmanned aerial vehicle (UAV) formation plays a pivotal role in diverse civil and military applications. In civil use, it can revolutionize tasks like precision agriculture, mapping vast landscapes, and enhancing emergency response. In the military, coordinated UAV formations are essential for strategic surveillance and tactical operations. Currently, much of the UAV formation research has been restricted to obstacle-free scenarios. However, the evolving landscape of modern missions demands UAVs to proficiently handle complex terrains. To overcome the hurdles of formation flight in such complex settings, scholars have proposed an array of methods. Control-based ones emphasize maintaining UAV stability and coordination, while trajectory optimization-based methods seek optimal flight paths. Our novel formation planning method combines multi-agent trajectory prediction and optimization. By integrating prediction outcomes into the optimization objective function, it achieves the dual goals of obstacle avoidance and formation integrity. Compared to prior techniques, our method stands out. It bolsters formation maintenance, ensuring UAVs stay in sync even amidst disruptions. Moreover, it streamlines the optimization process, saving computational time and resources. With this inventive approach, UAV formation flights in complex, obstacle-ridden environments will be more dependable and efficient. It paves the way for enhanced mission success rates and broader application possibilities, opening new vistas for UAV technology utilization.