Moises Granados-Cruz
Papers
1
Total Citations
3
H-Index
1
About
Moises Granados-Cruz is a researcher focused on robotics and autonomous systems, with a particular emphasis on sensor fusion and localization algorithms for mobile robots. His most-cited work, "Triangulation-based indoor robot localization using extended FIR/Kalman filtering" (2014), introduces a novel combined extended finite impulse response (EFIR) and Kalman filtering approach for improving indoor robot positioning through triangulation. A key contribution of this research is the EFIR algorithm’s ability to operate effectively without requiring precise knowledge of noise statistics—a common challenge in real-world engineering applications. This innovation offers a more robust and practical solution for robot localization in uncertain environments. While his citation count remains modest, Granados-Cruz’s work represents a meaningful step toward simplifying and enhancing the reliability of autonomous navigation systems, particularly in indoor settings where GPS is unavailable. His research contributes to the broader fields of robotics, control systems, and signal processing, with potential applications in warehouse automation, service robots, and industrial inspection.
Research Focus
Key Achievements
Top Papers
- 1