Khairunnas Khairunnas
Papers
1
Total Citations
23
H-Index
1
About
Khairunnas Khairunnas is an emerging researcher in the fields of robotics and computer vision, with a particular focus on object detection for mobile robotic systems. Their most cited work, "Pembuatan Modul Deteksi Objek Manusia Menggunakan Metode YOLO untuk Mobile Robot" (2021), has garnered 23 citations, demonstrating its relevance in the growing field of lightweight, real-time detection algorithms for autonomous platforms. This contribution addresses the critical challenge of enabling mobile robots to accurately identify human subjects using the efficient YOLO (You Only Look Once) framework, making robotics more accessible for beginners and advancing practical applications in human-robot interaction. Khairunnas's research supports the broader development of Indonesian-made mobile robots for diverse functions, from service robotics to assistive technologies. While still early in their career, their work reflects a dedication to bridging computer vision and robotics, offering valuable resources for students and practitioners entering the field. Their contributions highlight the importance of modular, cost-effective solutions in democratizing robotics education and innovation.
Research Focus
Key Achievements
Top Papers
- 1