Sattam Al Otaibi
Papers
1
Total Citations
34
H-Index
1
About
Dr. Sattam Al Otaibi is a leading researcher in intelligent robotics and adaptive control systems, with a particular focus on enhancing precision in industrial automation. His most cited work introduces a groundbreaking cognitive joint angle compensation system that leverages a self-feedback fuzzy neural network with incremental learning capabilities. This innovation directly addresses the critical challenge of joint angle errors in robotic arms—errors that significantly compromise end-effector accuracy in manufacturing and assembly tasks. By enabling real-time, online error compensation without requiring complete system retraining, Dr. Al Otaibi’s approach represents a major advance in adaptive robotics, offering a practical solution for maintaining high precision in dynamic industrial environments. His paper on this topic has garnered 34 citations, reflecting its influence on both academic research and practical engineering applications. Dr. Al Otaibi’s contributions are particularly notable for bridging the gap between theoretical neural network models and real-world robotic control, making his work essential reading for students and researchers in mechatronics, artificial intelligence, and industrial automation.
Research Focus
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Top Papers
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