Lukas Schichler
Papers
4
Total Citations
19
H-Index
2
About
Lukas Schichler is an emerging researcher specializing in autonomous robotics, robust localization, and intelligent path planning, with a particular focus on deploying autonomous systems in challenging and hazardous environments. His work addresses some of the most pressing limitations facing autonomous vehicles and rescue robots today — namely, reliable navigation where conventional sensors fail. Schichler's most impactful contribution to date is his development of multi-sensor fusion frameworks that combine thermal imaging, LiDAR, and GNSS data to achieve dependable localization in GNSS-denied settings such as tunnels and urban disaster zones. This research, which has garnered 8 citations since its 2025 publication, holds significant promise for search and rescue robotics. Complementing this, his thermal-LiDAR fusion work further refines localization under low-visibility conditions, directly tackling real-world operational constraints. On the planning side, Schichler has proposed a cost-effective smooth A* path planning algorithm tailored for non-holonomic car-like vehicles, accumulating 9 citations across related publications and demonstrating practical applicability in intelligent transportation systems. Together, his contributions form a coherent research vision: making autonomous systems genuinely reliable where they are needed most.
Research Focus
Key Achievements
Top Papers
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