Distributed control and real-engine simulators for choreographies of nano-quadrotors

In recent decades, distributed control has increasingly played a central role in the control community. Distributed control offers several advantages over centralized control, including improved scalability, fault tolerance, and flexibility. A recently emerging field of interest lies within the area of the arts, where distributed autonomous systems are employed within theatrical performances, offering new perspectives previously unimaginable. This application holds great promise as it offers performers complete freedom of movement, with each agent adapting to the environment. In contrast to many existing setups where drones follow predefined choreography, placing the burden of adaptation on the performers, this innovative approach ensures that technology aligns with the artistic vision. In line with this trend, the objective of this thesis is to explore the potential of an application in the performative field where humans and drones can interact within a shared environment. An online distributed optimization algorithm has been developed to fit this case study. A software implementation has been done using Python, ROS 2, and Webots simulator. Several experiments have been done, both in a real framework and in a simulated one, to prove the effectiveness of the algorithm and to tune the weights of the cost functions.