Constantin Wellhausen
Papers
1
Total Citations
9
H-Index
1
About
Constantin Wellhausen is a researcher advancing the frontiers of autonomous driving and mobile robotics, with a primary focus on robust multi-sensor odometry and state estimation. His most-cited work, "Kalman Filter with Moving Reference for Jump-Free, Multi-Sensor Odometry with Application in Autonomous Driving" (2020), addresses a critical challenge in autonomous navigation: eliminating discontinuities—or "jumps"—in vehicle pose estimates that plague global localization systems like INS/GNSS and SLAM. By introducing a moving reference frame within a Kalman filter framework, Wellhausen enables jump-free, continuous relative localization, a foundational capability for reliable control, tracking, and obstacle detection in autonomous cars. This contribution has garnered 9 citations, reflecting its practical relevance for engineers developing safe, real-world autonomous systems. His work bridges the gap between theoretical estimation algorithms and deployment-ready solutions, ensuring that odometry remains stable even when global corrections fail. For students and researchers, Wellhausen’s research exemplifies how careful sensor fusion can resolve persistent instabilities in autonomous navigation, making him a notable figure in the pursuit of dependable self-driving technology.
Research Focus
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Top Papers
- 1