Karl–Friedrich Kraiss
Papers
6
Total Citations
45
H-Index
4
About
Karl-Friedrich Kraiss is a pioneer in vision-based mobile robotics, with a career focused on enabling robots to perceive, navigate, and operate autonomously in indoor environments. His core research spans computer vision, scene analysis, and human-robot interaction, where he has developed landmark detection and self-localization techniques that allow robots to interpret natural structures—such as doors and floors—from monocular images. Kraiss’s most cited work (18 citations) introduces a vision-based landmark extractor for goal-oriented navigation, while his innovative approach to self-localization (11 citations) compares real camera snapshots with virtual images from a 3D environment model, bridging the gap between simulation and reality. He also advanced intelligent mobile sensor systems for indoor monitoring (7 citations) and designed a control center that leverages virtual reality for mission management and operator situational awareness. Though his citation counts are modest, Kraiss’s contributions are foundational for practical, low-cost robotic navigation, demonstrating how a priori knowledge and virtual environments can enhance real-world robot autonomy. His work remains relevant for researchers in mobile robotics, computer vision, and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Vision-Based Indoor Scene Analysis for Natural Landmark Detection18 citations · 2006
- 2Vision-based self-localization of a mobile robot using a virtual environment11 citations · 2003
- 3Monitoring indoor environments using intelligent mobile sensors7 citations · 2002
- 4Ein Leitstand zur Einsatzplanung und Überwachung mobiler Roboter4 citations · 1999
- 5A mobile robot control centre for mission and data management3 citations · 2002
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