P. Daniel Sutopo
Papers
1
Total Citations
31
H-Index
1
About
P. Daniel Sutopo is a leading researcher in robotics and computer vision, with a particular focus on real-time object detection for autonomous systems. His work centers on integrating deep learning techniques into robotic platforms, most notably in the domain of humanoid robot soccer. Sutopo’s major contribution lies in advancing the application of the You Only Look Once (YOLO) framework for rapid, accurate detection of dynamic objects—such as balls and goals—in competitive, real-time environments. His influential 2017 paper, "The deep learning development for real-time ball and goal detection of barelang-FC," has earned 31 citations, underscoring its impact on the robotics and computer vision communities. This work not only enhanced the perceptual capabilities of humanoid robots but also demonstrated the practical viability of deep learning in resource-constrained, latency-sensitive settings. Sutopo’s research bridges the gap between theoretical object detection models and their deployment in interactive robotics, making him a key figure in the evolution of intelligent, vision-guided autonomous agents. His achievements continue to inspire students and researchers exploring the intersection of AI and robotics.
Research Focus
Key Achievements
Top Papers
- 1