Thomas Wodtko
Papers
2
Total Citations
9
H-Index
2
About
Thomas Wodtko is a researcher advancing the frontiers of autonomous systems, with key contributions in sensor calibration, environment perception, and robust motion planning. His work addresses critical challenges in deploying autonomous robots and vehicles in complex, real-world environments. Wodtko’s most impactful paper, "Extrinsic Infrastructure Calibration Using the Hand-Eye Robot-World Formulation" (2023, 7 citations), introduces a certifiably globally optimal solution for calibrating multiple infrastructure sensors simultaneously. This work is notable for enabling geo-referenced calibration from vehicle motion data, a breakthrough for large-scale intelligent infrastructure. In his 2024 paper (2 citations), Wodtko tackles the persistent problem of conflicting LiDAR measurements in evidential grid maps, developing self-assessment methods that enhance the reliability of environment representations for motion planning. These contributions are vital for ensuring safety and robustness in autonomous navigation. By fusing theoretical rigor with practical sensor fusion techniques, Wodtko is shaping how autonomous systems perceive and interact with their surroundings, laying groundwork for more trustworthy self-driving and robotic technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2Self-Assessment of Evidential Grid Map Fusion for Robust Motion Planning2 citations · 2024