Reizano Amri Rasyid
Papers
1
Total Citations
3
H-Index
1
About
Reizano Amri Rasyid is a researcher specializing in mobile robotics and advanced estimation techniques, with a particular focus on improving autonomous navigation systems. His key research areas include sensor fusion, state estimation, and the application of Kalman filtering methods to robotic platforms. Rasyid’s most notable contribution is his work on the "Estimasi Posisi Mobile Robot Menggunakan Metode Akar Kuadrat Unscented Kalman Filter (AK-UKF)," which addresses the critical challenge of accurately estimating a mobile robot’s position using GPS data. By implementing the square-root unscented Kalman filter, he enhanced numerical stability and precision in position estimation, a vital improvement for robots operating in hazardous environments where human replacement is necessary. This work, cited 3 times, underscores his impact in refining localization algorithms for real-world robotic applications. Rasyid’s research bridges theoretical filtering methods and practical deployment, offering safer and more reliable autonomous systems. His achievements highlight a dedication to advancing mobile robot autonomy, making his work a valuable reference for students and researchers exploring robust state estimation in robotics.
Research Focus
Key Achievements
Top Papers
- 1