Khairul Annuar Abdullah
Papers
2
Total Citations
4
H-Index
2
About
Dr. Khairul Annuar Abdullah is a robotics researcher specializing in inverse kinematics, neural network modeling, and trajectory optimization for industrial robotic arms. His work addresses critical challenges in real-world automation, including end-effector accuracy, redundant movement, and heavy payload manipulation. In his 2020 study, he developed trigonometric tangential mathematical models for inverse kinematic control and trajectory tracking, enabling more precise and repeatable robotic motion under complex operational constraints. His 2018 paper pioneered a spreadsheet-based neural network framework for training and predicting inverse kinematics of two-degree-of-freedom planar robot arms, utilizing generalized reduced gradient optimization to minimize joint angle errors. Though his citation counts are early-stage (2 citations each), these contributions demonstrate a practical, accessible approach to bridging simulation and real-world robotic control. Dr. Abdullah’s work is particularly notable for its emphasis on low-cost, computationally efficient solutions—such as leveraging common spreadsheet software for neural network modeling—making advanced robotics techniques more accessible to developing research communities. His research holds promise for improving industrial automation in resource-constrained settings, with potential applications in manufacturing, assembly, and material handling.
Research Focus
Key Achievements
Top Papers
- 1
- 2