Muhammad Taufik Roseno

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About

Muhammad Taufik Roseno’s research centers on intelligent control systems for autonomous mobile robots, with a particular focus on navigation in dynamic and uncertain environments. His major contribution lies in the design and validation of neural network-based controllers that enable mobile robots to navigate safely and complete assigned tasks without human intervention. His most cited work, “Neural network controller design for a mobile robot navigation; A case study” (2017, 15 citations), demonstrates the practical application of artificial intelligence to overcome the core challenge of autonomous navigation—adapting to unpredictable surroundings in real time. A related study (2017, 3 citations) further explores this approach, reinforcing his commitment to bridging theoretical AI methods with real-world robotic systems. Roseno’s work is particularly valuable for students and researchers in robotics and control engineering, as it provides a clear case study of how neural networks can be implemented to enhance robot autonomy. His findings offer a foundation for developing more robust, adaptive navigation systems, making his research a useful reference for those exploring AI-driven solutions in mobile robotics.