New Research Tackles the Control Problem for Drone Swarms

<p>Swarms of Unmanned Aerial Vehicles (UAVs, or drones) are envisioned to transform various fields, from emergency response to law enforcement and military operations. Drone swarms provide scalable, adaptable, and decentralized solutions for dynamic work environments. However, the successful integration of these multi-agent systems into real-world settings presents significant challenges, particularly in terms of how humans can safely and effectively interact with and control these systems. Human-Swarm Interaction (HSI) aims to address these challenges by exploring how human operators can manage multiple drones in a cohesive manner, even under highly complex, uncertain conditions.</p><p>This thesis studies the problem of designing effective interaction mechanisms and interfaces for human operators to command drone swarms, specifically addressing challenges such as managing a large number of drones, supporting operators’ situational awareness, and balancing between centralized and decentralized control. The research highlights the necessity of rethinking conventional approaches by introducing alternative conceptual models, such as the "choir" metaphor, which re-imagines drone swarms as coordinated, semi-centralized ensembles rather than purely emergent, decentralized collectives. This metaphor aims to balance the collective, often unpredictable behavior of drone swarms with the predictable, directed actions needed in operational environments. By demonstrating how this metaphor can be operationalized in an HSI system architecture, the thesis provides new avenues for conceptualizing human interaction with autonomous systems.</p><p>Using a design research approach incorporating multiple-case study and scenario-based design activities to envision future swarm application in dialogue with prospective end users, the thesis develops and evaluates prototypes that embody these nuanced HSI concepts. The interface prototypes draw design inspiration from Real-Time Strategy (RTS) games. These elements include group commands, high-level mission planning, and resource pooling to create a hybrid interaction model that allows operators to maintain both a broad overview and precise control of multiple autonomous and collaborating drones. Domain expert evaluations of these prototypes in contexts such as firefighting and airport management validate the practical utility of these concepts.</p><p>The findings emphasize the value of adopting a Human-Technology-Organization (HTO) perspective in the design of HSI systems. Rather than focusing solely on the interaction between humans and technology, this systems-thinking approach acknowledges that drone swarms must be integrated into larger organizational frameworks, such as emergency response command structures or airport ground operations teams. It demonstrates that successful deployment requires accounting for the broader organizational context, including roles, workflows, and coordination needs. This holistic approach to HSI system design ensures that drone swarms not only meet technical performance criteria, such as reliability, responsiveness, and scalability, but also align with human and organizational needs, facilitating their adoption and effective use in a wide range of real-world scenarios. Ultimately, these contributions are intended to bridge the gap between theoretical models of swarm control and practical deployment, advancing both the field of HSI and the broader adoption of drone swarm technologies.</p>