About

Stefan Leutenegger is a leading researcher in mobile robotics, computer vision, and autonomous systems, whose work has fundamentally advanced the state of the art in simultaneous localization and mapping (SLAM) and visual-inertial odometry. He is perhaps best known for pioneering keyframe-based visual-inertial odometry using nonlinear optimization — a paradigm-shifting approach that replaced traditional filtering methods and has since become a foundational technique in the field, accumulating nearly 1,700 citations. His research extends naturally into richer scene understanding, exemplified by SemanticFusion (657 citations), which integrated convolutional neural networks with dense 3D mapping to endow robots with semantic environmental awareness. Leutenegger has also made significant contributions to object-level dynamic SLAM, legged robot state estimation, and event-based vision — his survey on event cameras (633 citations) serving as an essential reference for the community. His practical engineering contributions, including hardware-software sensor systems for micro aerial vehicles and UAV-based industrial inspection platforms, bridge fundamental research and real-world deployment. Most recently, his work on aerial additive manufacturing (238 citations) demonstrates a bold expansion into multi-robot construction. Across more than a decade of research, Leutenegger's portfolio reflects both rigorous theoretical depth and a consistent drive toward autonomous systems capable of operating intelligently in complex, dynamic environments.

Research Focus

Key Achievements

24
H-Index
56
Papers
6,028
Total Citations
108
Avg Citations/Paper
🏆 Most Cited Paper
Keyframe-based visual–inertial odometry using nonlinear optimization
1,697 citations · 2014
📈 Most Prolific Year: 2024 (7 Papers)
🤝 Key Collaborators: 186
🏛 Institutions: ETH Zurich, Dyson (United Kingdom), Imperial College London, Board of the Swiss Federal Institutes of Technology, Autonomous Healthcare, Robotics Research (United States)

Top Papers

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    Event-Based Vision: A Survey
    633 citations · 2020
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Key Collaborators

Contact & Links

Available for collaboration
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