Stef Van Havermaet

Papers

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About

Stef Van Havermaet’s research lies at the intersection of swarm robotics and bio-inspired exploration, with a primary focus on shepherding—the autonomous guidance of herds in dynamic environments. His major contributions advance the fundamental challenge of enabling robots to efficiently steer groups of autonomous agents, such as animals or crowds, toward safety or desired destinations. In his most-cited work, “Collective Lévy Walk for Efficient Exploration in Unknown Environments” (2018, 13 citations), Van Havermaet introduced a novel search strategy inspired by animal foraging patterns, demonstrating how Lévy walks can optimize multi-robot exploration in uncharted terrains. This foundational study paved the way for his subsequent shepherding research. His 2023 paper, “Steering herds away from dangers in dynamic environments” (10 citations), directly addresses real-world applications like crowd control and rescue operations, proposing reactive algorithms that allow robots to guide herds while avoiding obstacles. More recently, his 2024 work, “Reactive shepherding along a dynamic path” (5 citations), refines these techniques for path-following tasks. Van Havermaet’s impact is evident in the practical relevance of his work, which bridges theoretical swarm intelligence and deployable robotic systems, offering scalable solutions for emergency evacuation and animal herding. His achievements highlight a commitment to translating complex biological principles into robust, real-world robotic behaviors.