Rangga Dikarinata
Papers
2
Total Citations
6
H-Index
2
About
Rangga Dikarinata is a robotics researcher specializing in computer vision and real-time object detection for autonomous soccer robots. His work centers on improving the computational efficiency and accuracy of ball detection and tracking systems, particularly for wheeled soccer robots competing in national contests like the Wheeled Indonesian Soccer Robot Contest (Wheeled KRSBI). Dikarinata’s key contributions include developing a region-of-interest (ROI) search method that reduces processing load during ball detection, as detailed in his most-cited paper, “Searching Ball Around ROI to Increase Computational Processing of Detection” (2020, 4 citations). This work enhances the performance of the EEPIS Robot Soccer On Wheeled (ERSOW) platform, which relies on artificial intelligence for ball detection, dribbling, and opponent avoidance. He also advanced dynamic tracking with “Dynamic Local Ball Tracking in Middle Size League Robot Soccer ERSOW based on Kalman Filter” (2020, 2 citations), addressing the heavy computational demands of vision-based object detection. By optimizing detection processes, Dikarinata has helped improve robot responsiveness and reliability in competitive settings. His research is valuable for students and engineers working on real-time vision systems, autonomous navigation, and robotics competitions, demonstrating how targeted algorithmic improvements can significantly enhance robotic performance under constrained processing environments.
Research Focus
Key Achievements
Top Papers
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- 2