Decentralized Acceleration-Based Bird-Inspired Flocking

In the following, we analyze and discuss the implementation of a novel approach for distributed flocking behavior applied to a group of Uncrewed Aerial Vehicle (UAV)s, also referred to as drones. Inspired by natural flocking phenomena observed in birds, which demonstrate coordinated movement in response to internal and external stimuli, we tackle the problem of robust and dynamic aerial motion for robots and design a control law based on a novel physical model. In contrast to previous works that rely on velocity or position-based references, this approach leverages an acceleration-based law to describe the collective dynamics of many interacting particles. As observed in the following, a third-order control possesses several advantages compared to first or second-order control, such as smoother transitions, better force balancing, and more responsive and dynamic behaviors. These advantages are thoroughly analyzed in the following, thanks to physics-based realistic simulations and field experiments with medium-sized UAVs in an unstructured outdoor environment.