Faruk Dautovic
Papers
1
Total Citations
4
H-Index
1
About
Faruk Dautovic’s research centers on mobile robotics, with a particular focus on localization, sensor fusion, and robotic vision. His most-cited work, “Localization of holonomous mobile robot HOLBOS using extended Kalman filter (EKF) and robotic vision” (2013, 4 citations), tackles the fundamental challenge of determining a robot’s position in real time. Dautovic’s key contribution lies in comparing and integrating two distinct localization approaches—odometry-based and landmark-based—using an Extended Kalman Filter to enhance accuracy. This work demonstrates his ability to combine theoretical algorithms with practical implementation, as seen in the HOLBOS platform. While his citation count is modest, his research addresses a core problem in autonomous navigation, laying groundwork for more robust mobile robot systems. Dautovic’s achievement lies in bridging classical odometry with vision-based landmark recognition, a dual-method strategy that remains relevant for researchers exploring sensor fusion in robotics. His work is particularly valuable for students and engineers seeking clear, applied examples of EKF localization in real-world robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1