Muhidin Hujdur

Papers

Total Citations

H-Index

About

Muhidin Hujdur’s research centers on mobile robotics, with a particular focus on localization, sensor fusion, and autonomous navigation. His most cited work, “Localization of holonomous mobile robot HOLBOS using extended Kalman filter (EKF) and robotic vision” (2013), tackles the fundamental challenge of determining a robot’s position in real time. By integrating odometry and landmark-based localization through an Extended Kalman Filter, Hujdur demonstrated a robust method for reducing positional uncertainty in holonomous platforms. This contribution is critical for applications requiring precise, continuous motion, such as automated warehouses or service robots. Although his citation count is modest—with the flagship paper accruing 4 citations—his work represents a practical, systems-level approach to a core robotics problem. Hujdur’s research bridges theoretical estimation techniques with real-world implementation, offering a clear example of how sensor data fusion can enhance robotic autonomy. For students and researchers entering the field, his study of the HOLBOS robot serves as an accessible case study in the trade-offs between computational efficiency and localization accuracy, underscoring the enduring relevance of EKF-based methods in mobile robotics.