Kevin Egger
Papers
1
Total Citations
270
H-Index
1
About
Kevin Egger is a leading researcher in robotics, with a primary focus on visual-inertial mapping, localization, and SLAM (Simultaneous Localization and Mapping). His most impactful contribution is the development of *maplab*, an open-source framework that has become a cornerstone for research in robust visual-inertial estimation. This framework, detailed in his highly cited 2018 paper (over 270 citations), enables researchers to build, manage, and optimize multi-session maps, allowing robots to localize against prior environments and achieve drift-free pose estimates. By providing a modular, accessible platform, Egger has significantly lowered the barrier to entry for complex mapping research, accelerating progress across the field. His work directly addresses critical challenges in long-term autonomy, where reliable localization over time and space is essential. Through maplab, Egger has not only advanced the state of the art but also empowered a generation of roboticists to explore new frontiers in navigation and perception.
Research Focus
Key Achievements
Top Papers
- 1