CAREER: Transferring biological networks emergent principles to drone swarm collaborative algorithms

Consider scenarios like search and rescue operations or large-scale environmental monitoring where drones must autonomously navigate, adapt to dynamic obstacles, and collaboratively optimize their actions. In the field of cyberphysical systems, the challenge intensifies when striving for decentralized decision-making. The successful development of these algorithms can produce potentially transformative paradigms for applications critical to societal welfare. Remarkably, organisms in nature, such as slime molds and fungi, are able to develop decentralized, coordinated networks that optimize transport better than engineers, solve mazes, detect masses at a distance, or even memorize periodic events. This approach is pivotal in addressing dynamic environmental conditions and ensuring scalability as the swarm size expands. This research aims to develop novel collaborative organization algorithms for drone swarms by leveraging advanced computational frameworks that mimic the functionalities of biological networks. Our strategy involves transferring collective behavior insights from network-forming organisms to formulate rules for individual drones. The proposal addresses critical knowledge gaps in swarm collaborative algorithms, focusing on the scientific challenge of understanding the principles guiding the transition from microscale to macroscale swarm behavior. On the engineering front, it aims to develop robust machine learning procedures for accurately transferring observed behaviors to synthetic systems and enhance supercomputing capabilities for improved scalability. The novelty lies in adopting a bottom-up biological perspective, mapping simulation data showcasing emergence to the computational and communication constraints of a drone swarm. Additionally, this project fills critical educational gaps in the public understanding of swarm coordination and emergent behavior in engineering. The initiative's open-source tools aim to accelerate basic research in swarm mechanics and enhance STEM education at various levels. With a focus on translating complex concepts into everyday language, the project impacts the next generation of STEM engineers through specialized courses, virtual experiences like "Swarm Quest", and also targets the general public with exhibitions like "Are you smarter than a slime mold?", aimed at the youngest audience. The initiative involves mentoring a high-school teacher in Pennsylvania, graduate and undergraduate students at Penn State, and the creation of free instructional material on the concept of emergence in cyberphysical systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.