Ahmad Fauzan Kadmin
Papers
1
Total Citations
8
H-Index
1
About
Ahmad Fauzan Kadmin is a researcher whose work lies at the intersection of computer vision, robotics, and autonomous navigation. His key contributions center on developing practical, implementable solutions for stereo vision systems, particularly for mobile robot guidance. His most cited paper, "A practical method for camera calibration in stereo vision mobile robot navigation" (2012, 8 citations), introduces a streamlined calibration approach using the Jean-Yves Bouguet toolbox to extract intrinsic and extrinsic parameters from stereo camera pairs. This method directly enables accurate image rectification, a critical step for depth perception and spatial mapping in autonomous robots. Kadmin’s work is notable for its emphasis on real-world applicability, bridging the gap between theoretical calibration models and the constraints of field robotics. By providing a reliable, accessible calibration pipeline, his research has supported the development of more robust stereo vision systems for navigation tasks. His contributions are particularly valuable for students and engineers seeking to implement stereo vision in resource-constrained or mobile platforms, offering a clear, proven methodology that continues to inform practical robotics applications.
Research Focus
Key Achievements
Top Papers
- 1