Milad Roigari
Papers
1
Total Citations
33
H-Index
1
About
Milad Roigari is a leading researcher in mobile robotics, with a core focus on sensor fusion, localization, and autonomous navigation. His most cited work, "Multiple sensor fusion for mobile robot localization and navigation using the Extended Kalman Filter" (2015, 33 citations), presents a pioneering approach to integrating data from encoders, compasses, IMUs, and GPS. By applying an Extended Kalman Filter (EKF) across three distinct fusion strategies, Roigari significantly enhanced the accuracy and robustness of robot pose estimation in real-world environments. He further advanced the field by coupling this localization framework with input-output state feedback linearization (I-O SFL), enabling precise trajectory tracking and control. This dual contribution—robust multi-sensor fusion and nonlinear control—has become a foundational reference for researchers developing autonomous ground vehicles and mobile manipulators. Roigari’s work is particularly valued for its practical, implementation-ready solutions, bridging the gap between theoretical estimation and real-time navigation. With 33 citations, his research continues to influence modern robotics curricula and autonomous systems design, solidifying his reputation as a key contributor to intelligent mobile robot navigation.
Research Focus
Key Achievements
Top Papers
- 1