Victor Reijgwart
Papers
15
Total Citations
390
H-Index
8
About
Victor Reijgwart is a robotics researcher whose work sits at the intersection of autonomous exploration, multi-robot systems, and 3D mapping. He is best known for his pivotal contributions to the CERBERUS team, which won the prestigious DARPA Subterranean Challenge in 2021 — a landmark achievement in field robotics. His research on coordinating legged and aerial robots for autonomous subterranean exploration has garnered considerable attention, with related publications accumulating over 200 citations collectively, reflecting their significant influence on the robotics community. Reijgwart has made notable advances in volumetric mapping, developing wavelet-based compression techniques that enable efficient, multi-scale environmental representation — work that directly supports path planning, exploration, and reactive obstacle avoidance in resource-constrained systems. His contributions to maplab 2.0 further demonstrate his expertise in multi-modal SLAM frameworks that integrate diverse sensor modalities and deep learning to achieve robust localization. He has also tackled the practical challenge of odometry drift during large-scale exploration, proposing unified approaches that maintain mission integrity even under severe state estimation uncertainty. From underground mines to autonomous racing, Reijgwart's research consistently bridges theoretical rigor with real-world deployment, making him a compelling figure in modern autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 3maplab 2.0 – A Modular and Multi-Modal Mapping Framework57 citations · 2022
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- 8AMZ Driverless: The full autonomous racing system11 citations · 2020
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