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About

Panus Nattharith is a robotics researcher whose work centers on autonomous mobile robot navigation, with a particular emphasis on hybrid control architectures that blend deliberative planning with reactive, behavior-based systems. His most impactful contribution, "Machine vision and fuzzy logic-based navigation control of a goal-oriented mobile robot" (17 citations), introduces a framework where a monocular camera feeds visual data into a fuzzy logic controller, enabling a robot to intelligently pursue a goal while avoiding obstacles. This work is complemented by his influential case study on the iRobot Roomba platform (10 citations), which demonstrated how low-cost, off-the-shelf hardware can be transformed into a sophisticated testbed for hybrid navigation control. Nattharith has also advanced practical sensing techniques, developing a low-cost mobile robot platform with custom infrared sensor arrays for obstacle detection, and proposing a novel method for monocular distance estimation using SIFT features and neural networks. His research is notable for its pragmatic approach—combining theoretical control strategies with accessible hardware—making it particularly valuable for students and researchers seeking to implement autonomous navigation systems without expensive equipment.