Nature offers countless examples of how individual abilities can be amplified through collaboration. Birds flock together to conserve energy during migration, and fish school in large groups to evade predators—these collective behaviors inspire our work in creating autonomous UAV swarms capable of tackling complex real-world problems. By studying and replicating the principles of collective motion and emergent sensing, we explore how simple local interactions among agents can lead to sophisticated group dynamics that exceed the capabilities of any single robot. Our research includes a range of methods and experiments, from kinematic and dynamic simulations to real-world UAV trials, demonstrating how these swarms can navigate, interact, and collaborate to achieve tasks that would be impossible individually. Throughout this work, we introduce and refine methods for emergent sensing within flocking autonomous robots, systematically establishing the technological steps needed for their implementation. By investigating the nature of this behavior from multiple perspectives, we lay a robust foundation for advancing swarm robotics.
More information on the thesis