Thiang
Papers
1
Total Citations
11
H-Index
1
About
Dr. Thiang is a researcher in robotics and artificial intelligence, with a primary focus on applying neural network techniques to solve complex problems in robotic manipulation. Their most cited work, "Artificial Neural Network With Steepest Descent Backpropagation Training Algorithm For Modeling Inverse Kinematics Of Manipulator" (2009, 11 citations), addresses a fundamental challenge in robotics: deriving inverse kinematic equations for multi-degree-of-freedom manipulators. This contribution demonstrates how artificial neural networks can effectively model and compute inverse kinematics, offering a practical alternative to traditional analytical methods that become increasingly difficult as robot complexity grows. The work highlights Dr. Thiang's expertise in combining neural network architectures with backpropagation training algorithms to create robust models for robotic control systems. While their citation count reflects a focused, specialized contribution to the field, this research provides valuable insights for students and researchers working on robot manipulator control, particularly those seeking computational approaches to kinematic modeling. The paper serves as a practical reference for implementing neural network-based solutions in robotics applications.
Research Focus
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Top Papers
- 1