Zulfatman Has
Papers
3
Total Citations
24
H-Index
2
About
Zulfatman Has is a researcher specializing in computer vision, autonomous robotics, and intelligent systems, with a particular focus on the development of soccer robots capable of perceiving and interacting with their environments. His most recognized contribution centers on the application of omnidirectional vision systems enhanced by Particle Swarm Optimization (PSO) and neural networks for real-time object detection — a technically demanding challenge that requires robots to accurately identify objects such as balls, goalposts, and field markings while simultaneously estimating distances and angles. This work, published in 2018, has accumulated over 24 citations across multiple venues, reflecting meaningful engagement from the robotics and machine learning communities. By combining bio-inspired optimization techniques with neural network architectures, Zulfatman Has demonstrated a practical and computationally efficient approach to autonomous robot perception — a problem with broad implications for human-robot interaction and competitive robotics platforms like RoboCup. His research sits at an important intersection of applied artificial intelligence and embedded systems, making it particularly relevant for students and engineers working on intelligent mobile robots and vision-based autonomous systems.
Research Focus
Key Achievements
Top Papers
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