Ahmad Fahrurozi
Papers
1
Total Citations
2
H-Index
1
About
Ahmad Fahrurozi is a researcher in robotics and computer vision, with a focused interest in autonomous systems and real-time object detection. His work centers on enhancing the perceptual capabilities of wheeled robots, particularly in dynamic environments like robot soccer. His most cited paper, "Ball Identification and Localization using Regression for Wheeled Robot Soccer" (2021), addresses a critical challenge in robotic sports: accurately identifying and localizing the ball in real time. Fahrurozi’s contribution lies in developing a method that uses color filtering within the HSV color space combined with regression techniques, enabling robots to reliably detect and track the ball despite changing lighting conditions and motion. This work has garnered 2 citations, reflecting its niche but practical value in the field of robot soccer, where precision and speed are paramount. Fahrurozi’s research bridges the gap between theoretical computer vision algorithms and their deployment on resource-constrained robotic platforms, offering a scalable solution for autonomous navigation and interaction. His achievements underscore a commitment to advancing real-time visual processing, with potential applications beyond sports, such as in industrial automation and mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1