Noorman Rinanto
Papers
4
Total Citations
55
H-Index
3
About
Noorman Rinanto is a robotics researcher whose work focuses on the intersection of intelligent control systems and robotic manipulation. His most influential contribution is the development of a neural network-based inverse kinematic model for a 3-DOF arm drawing robot, a paper that has garnered 39 citations and demonstrates how artificial neural networks can solve complex movement calculations in real-time. He has also advanced autonomous navigation by applying Fuzzy Logic Controllers to wheeled soccer robots for obstacle avoidance, enabling them to operate effectively in dynamic, multi-agent environments. Beyond these core contributions, Rinanto has explored the classification of arm muscle signals using Support Vector Machines to improve manipulator control, and has engaged in educational outreach by training students in analog line tracer robotics to enhance STEM learning at the primary school level. With a research portfolio that spans neural networks, fuzzy logic, and machine learning for robotics, Rinanto’s work bridges theoretical control methods with practical applications in both competitive and educational robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Obstacle Avoidance using Fuzzy Logic Controller on Wheeled Soccer Robot11 citations · 2019
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