Kittipong Boonlong
Papers
2
Total Citations
13
H-Index
2
About
Kittipong Boonlong is a researcher whose work lies at the intersection of robotics, control systems, and computational intelligence. His primary research areas include robot arm movement control, model-based reinforcement learning (MBRL), and the application of machine learning and optimization techniques to complex mechanical systems. Boonlong’s most cited work, “Robot Arm Movement Control by Model-based Reinforcement Learning using Machine Learning Regression Techniques and Particle Swarm Optimization” (2023), has garnered 11 citations, showcasing his contribution to advancing precision and adaptability in robotic manipulation for fields ranging from industry to medicine and agriculture. Earlier, Boonlong explored friction compensation in robotic systems through a neuro-genetic hybrid framework (2002), integrating neural networks with genetic algorithms to improve closed-loop control performance. Though this foundational work has fewer citations, it reflects his sustained interest in hybrid intelligent systems for real-world engineering challenges. Boonlong’s research demonstrates a commitment to bridging theoretical optimization methods with practical robotic applications, making his work relevant for students and researchers in mechatronics, reinforcement learning, and intelligent control.
Research Focus
Key Achievements
Top Papers
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