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About

Xavier Duquesne is a robotics researcher specializing in the decentralized coordination and traffic control of robotic swarms. His work addresses a critical challenge in swarm robotics: the congestion that arises when numerous autonomous robots attempt to access a common target area simultaneously. Duquesne’s major contributions lie in defining and analyzing the fundamental limits of swarm efficiency in these scenarios. He introduced the concept of *maximum target area throughput*, a key metric for evaluating how effectively a swarm can access a shared space as its size scales. His most cited paper (2022, 10 citations) proposes novel congestion control algorithms that enable robots to self-regulate their approach, maximizing the flow into the target area without centralized oversight. This work, alongside his foundational study on throughput measures (2022, 5 citations), provides a theoretical and practical framework for designing scalable, high-performance swarms. By quantifying the trade-offs between swarm density and access efficiency, Duquesne’s research lays essential groundwork for future applications in automated logistics, search-and-rescue, and environmental monitoring, where large groups of robots must operate in constrained spaces.