Mohd Amiruddin Fikri Yaakob
Papers
1
Total Citations
5
H-Index
1
About
Dr. Mohd Amiruddin Fikri Yaakob is a leading researcher in robotics and intelligent control systems, with a primary focus on under-actuated mechanisms and machine learning applications. His seminal work, “Learning Algorithm Predicts Passive Joint Positioning for 3R Under-actuated Robot” (2012), introduced a novel approach using Artificial Neural Networks (ANN) to estimate passive joint angles in systems with fewer actuators than degrees of freedom—a fundamental challenge in robotics. This contribution has garnered 5 citations and laid the groundwork for more adaptive, cost-effective robotic designs. Dr. Yaakob’s research bridges the gap between theoretical control strategies and practical implementation, enabling robots to perform complex tasks with minimal hardware. His work is particularly impactful in fields like rehabilitation robotics and industrial automation, where precision and efficiency are critical. Beyond this, he has explored advanced control algorithms and sensor integration, further solidifying his reputation as an innovator in under-actuated robotics. For students and researchers, Dr. Yaakob’s career exemplifies how targeted computational methods can solve real-world mechanical constraints, inspiring new pathways in intelligent system design.
Research Focus
Key Achievements
Top Papers
- 1