Elliott Hogg

University of Bristol, Bristol Robotics Laboratory

Papers

Total Citations

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About

Elliott Hogg is a researcher specializing in the intersection of artificial intelligence, evolutionary robotics, and swarm intelligence. His primary research focuses on developing supervisory control mechanisms for robot swarms, particularly through the use of evolving behaviour trees. Hogg's most cited work, "Evolving behaviour trees for supervisory control of robot swarms" (2020, 14 citations), introduces novel methods for humans to provide effective guidance to autonomous swarms, addressing the critical challenge of real-world deployment where monitoring and intervention are essential. Building on this foundation, his 2022 paper "Evolving Robust Supervisors for Robot Swarms in Uncertain Complex Environments" (3 citations) extends these concepts to handle unpredictable conditions, demonstrating how adaptive supervisory controllers can maintain swarm performance despite environmental uncertainty. Hogg's contributions are particularly valuable for applications in search-and-rescue, environmental monitoring, and military operations, where reliable human-swarm interaction is paramount. His work represents a significant step toward practical, deployable swarm systems that can operate effectively under human supervision while maintaining autonomy in dynamic environments.