Drone formation flights, exemplified by performances such as the Intel Drone Shows, demonstrate the advancements and capabilities of current technology. This work revisits the concept of self-organization through swarm behavior for this goal, presenting PROTEASE 2.0 as an advanced approach in this domain. The proposed method facilitates parametrizable swarm behavior at a high level of abstraction. Building upon its predecessor, PROTEASE, it enables the generation of emergent effects through a single, generalized implementation, wherein only the parameters governing individual swarm members need to be adjusted. Leveraging swarm behavior for formation flight offers distinct advantages, including enhanced scalability, robustness, and flexibility. Unlike centrally coordinated approaches, swarm-based methods support the emergence of complex and dynamic formations. Notable formations include parallel swarms interacting with one another, single swarms utilizing multiple reference points to achieve novel flight patterns, and hierarchical swarm structures that further extend the range of possible configurations of swarm behavior. This paper introduces fundamental swarm behaviors that can be realized within the PROTEASE 2.0 framework in detail and explores their composition into more complex formations. The primary focus is the experimental and empirical evaluation of these concepts in simulated environments, including their stabilization properties when facing disturbances. In combination with previous successful pre-evaluations involving real drones it provides a strong foundation for future real-world applications of PROTEASE 2.0.
