Sean Owens

Papers

Total Citations

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About

Sean Owens is a pioneering researcher in multi-robot systems, with a focus on scalable coordination and human-robot interaction for large, dynamic teams. His work addresses the critical challenge of deploying robot swarms in real-world, time-sensitive scenarios, particularly in Urban Search and Rescue (USAR). Owens’ most influential contribution is the development of the "image queue" asynchronous display method, which enables human operators to efficiently sift through vast data streams from autonomous robot teams during foraging and search tasks—a paper that has garnered 26 citations for its practical impact on human-robot collaboration. He also introduced the LA-DCOP algorithm, a distributed task allocation framework designed to handle spatially distributed, dynamically appearing tasks in environments with limited communication, scaling to problems with far more tasks than robots. This work, cited 9 times, demonstrates his ability to tackle both theoretical and applied challenges in large-scale robot coordination. Owens’ research is notable for bridging the gap between algorithmic efficiency and real-world deployment, making him a key figure in advancing the capabilities of autonomous robot teams for critical missions.