Mohamad Afendee Mohamed

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About

Mohamad Afendee Mohamed is a researcher whose work lies at the intersection of robotics, intelligent control systems, and computational intelligence. His key research areas include adaptive neuro-fuzzy inference systems (ANFIS), robotic arm manipulation, and image processing for object detection. In his most cited work, "Colored object detection using 5 dof robot arm based adaptive neuro-fuzzy method," he demonstrated how ANFIS can be integrated with an Arduino microcontroller to enable a 5-degree-of-freedom robot arm to dynamically detect and respond to colored objects using MATLAB-based image processing. This contribution, with 26 citations, showcases his ability to bridge theoretical fuzzy logic with practical, real-time robotic applications. Mohamed’s work is notable for its hands-on, implementation-focused approach, making complex control systems accessible for educational and industrial prototyping. His research continues to influence the development of adaptive, sensor-driven robotic systems, offering valuable insights for students and engineers working on intelligent automation and embedded control.