Marius Fehr
Papers
16
Total Citations
693
H-Index
11
About
Marius Fehr is a robotics researcher specializing in visual-inertial mapping, autonomous exploration, and 3D scene understanding — areas at the forefront of modern mobile robotics. He is perhaps best known for his foundational contributions to **maplab**, an open-source framework for visual-inertial mapping and localization that has become a widely adopted research tool, accumulating over 270 citations since its 2018 release. Its successor, maplab 2.0, extended this work with modular, multi-modal SLAM capabilities, reflecting Fehr's sustained commitment to robust, scalable mapping systems. Fehr has also made significant contributions to 3D reconstruction, introducing TSDF-based change detection methods for long-term dynamic environments and contributing to the Voxblox planning framework. His work on hybrid topological-dense mapping addresses the real-world challenge of operating in large indoor spaces efficiently. A notable applied achievement is his involvement with the **CERBERUS** team in the DARPA Subterranean Challenge, where autonomous legged and aerial robots demonstrated complex underground exploration — work that has garnered over 100 citations. With a portfolio spanning sensor calibration, topological navigation, and open hardware design, Fehr's research consistently bridges theoretical innovation with practical robotic deployment, making him a valuable reference for students working in SLAM, autonomous navigation, and field robotics.
Research Focus
Key Achievements
Top Papers
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- 4maplab 2.0 – A Modular and Multi-Modal Mapping Framework57 citations · 2022
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- 8Voxblox: Building 3D Signed Distance Fields for Planning18 citations · 2016
- 9VersaVIS—an open versatile multi-camera visual-inertial sensor suite15 citations · 2020
- 10Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps15 citations · 2018