About

Laurent Kneip is a leading researcher in robotics and computer vision, whose work has fundamentally advanced the autonomous navigation of micro aerial vehicles (MAVs). His key research areas include geometric computer vision, visual odometry, and multi-camera systems for robotics. Kneip is best known for his pioneering contributions to vision-controlled micro flying robots, demonstrated in his highly cited work on autonomous navigation and mapping in GPS-denied environments (297 citations). He developed the widely-used OpenGV library (160 citations), a unified C++ framework for real-time calibrated geometric vision that has become a standard tool in the robotics community. His compendium on monocular vision for long-term MAV state estimation (239 citations) provides essential foundations for aerial robot localization. Kneip also made significant contributions to solving the generalized camera pose estimation problem, introducing efficient solutions to the NPnP problem (76 citations). His work on characterizing the Hokuyo URG-04LX laser range scanner (126 citations) has been instrumental for sensor integration in robotics. Through his leadership in the EU-funded SFly project, which developed swarms of autonomous micro flying robots, Kneip has helped shape the future of aerial robotics for search and rescue, surveillance, and environmental monitoring.

Research Focus

Key Achievements

11
H-Index
16
Papers
1,085
Total Citations
68
Avg Citations/Paper
🏆 Most Cited Paper
Vision-Controlled Micro Flying Robots: From System Design to Autonomous Navigation and Mapping in GPS-Denied Environments
297 citations · 2014
📈 Most Prolific Year: 2014 (3 Papers)
🤝 Key Collaborators: 42
🏛 Institutions: Australian National University, ETH Zurich, Friedrich-Alexander-Universität Erlangen-Nürnberg, ShanghaiTech University, Shanghai Institute of Microsystem and Information Technology

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago