Simon Lynen

About

Simon Lynen is a prominent robotics researcher whose work sits at the intersection of visual-inertial odometry, autonomous navigation, and simultaneous localization and mapping (SLAM). He is best known for pioneering contributions to sensor fusion techniques that combine visual and inertial measurements to achieve robust, real-time state estimation — challenges fundamental to autonomous systems operating in GPS-denied environments. His most influential work, "Keyframe-based visual–inertial odometry using nonlinear optimization" (2014), has accumulated nearly 1,700 citations, reflecting its foundational impact on the field. Lynen has been particularly instrumental in advancing navigation for Micro Aerial Vehicles (MAVs), developing onboard self-calibration systems and multi-sensor fusion frameworks that dramatically improved reliability and accuracy in real-world deployments. His open-source platform, Maplab (2018), further democratized research in visual-inertial mapping by providing the community with a flexible, extensible framework for localization tasks. Beyond state estimation, Lynen tackled the scalability challenges of long-term robot operation, contributing innovative map compression and lifelong localization strategies. With over 3,700 cumulative citations across his published work, his research has profoundly shaped modern autonomous robotics, particularly in making aerial robots smarter, lighter, and more capable in complex, unstructured environments.

Research Focus

Key Achievements

Top Papers

1. 1
   Keyframe-based visual–inertial odometry using nonlinear optimization

   1,697 citations · 2014
2. 2
   A robust and modular multi-sensor fusion approach applied to MAV navigation

   571 citations · 2013
3. 3
   Real-time onboard visual-inertial state estimation and self-calibration of MAVs in unknown environments

   421 citations · 2012
4. 4
   Vision-Controlled Micro Flying Robots: From System Design to Autonomous Navigation and Mapping in GPS-Denied Environments

   297 citations · 2014
5. 5
   Maplab: An Open Framework for Research in Visual-Inertial Mapping and Localization

   270 citations · 2018
6. 6
   Monocular Vision for Long‐term Micro Aerial Vehicle State Estimation: A Compendium

   239 citations · 2013
7. 7
   The gist of maps - summarizing experience for lifelong localization

   76 citations · 2015
8. 8
   Keep it brief: Scalable creation of compressed localization maps

   60 citations · 2015
9. 9
   Motion‐ and Uncertainty‐aware Path Planning for Micro Aerial Vehicles

   58 citations · 2014
10. 10
    Point cloud descriptors for place recognition using sparse visual information

    52 citations · 2016

Key Collaborators

Contact & Links