Rachmad Tri Soelistijono
Papers
2
Total Citations
24
H-Index
2
About
Rachmad Tri Soelistijono is a researcher specializing in artificial intelligence, robotics, and control systems, with a particular focus on autonomous mobile robots and assistive technologies. His work explores the application of neural networks, fuzzy logic, and machine learning to improve robotic autonomy and human-robot interaction. In his highly cited 2017 study, he compared back propagation neural networks and fuzzy logic controllers for wall-following autonomous mobile robots, demonstrating how these AI methods can enhance real-time navigation and decision-making. This paper has garnered 22 citations, reflecting its impact on the field of intelligent robotics. Soelistijono also investigated the use of extreme learning machines versus neural networks for hand typist robots designed to assist quadriplegic individuals, highlighting his commitment to developing accessible technologies for people with disabilities. His comparative analyses provide valuable insights into optimizing predictive accuracy and control in robotic systems. Through his research, Soelistijono contributes to advancing AI-driven robotics, making autonomous systems more efficient and inclusive.
Research Focus
Key Achievements
Top Papers
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