Agus Khumaidi
Papers
5
Total Citations
39
H-Index
2
About
Agus Khumaidi is a researcher specializing in robotics and artificial intelligence, with a focus on autonomous navigation, control systems, and assistive technologies. His work integrates machine learning and fuzzy logic to enhance robot performance in dynamic environments. In his most-cited paper (22 citations), he compares backpropagation neural networks and fuzzy logic controllers for wall-following autonomous mobile robots, demonstrating how these AI methods improve obstacle negotiation and path tracking. He further applies fuzzy logic to wheeled soccer robots for collision avoidance (11 citations), enabling real-time decision-making using omnidirectional vision and embedded processing. Khumaidi also explores neural network variants, comparing extreme learning machines with backpropagation for a hand-typing robot designed to assist quadriplegic individuals, highlighting his commitment to inclusive technology. His research extends to sports robotics, where he uses trigonometry to predict ball trajectories for soccer robot goalkeepers. Beyond technical development, Khumaidi engages in educational outreach, training students in line-tracer robotics to foster STEM skills at the primary school level. His work bridges theoretical AI methods with practical robotic applications, contributing to both competitive robotics and assistive devices.
Research Focus
Key Achievements
Top Papers
- 1
- 2Obstacle Avoidance using Fuzzy Logic Controller on Wheeled Soccer Robot11 citations · 2019
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