Mumu Komaro

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About

Mumu Komaro is a researcher in robotics and intelligent control systems, with a focus on integrating adaptive neuro-fuzzy methods into robotic manipulation and object detection. Their most cited work, "Colored object detection using 5 dof robot arm based adaptive neuro-fuzzy method" (2019, 26 citations), introduces an Adaptive Neuro-Fuzzy Inference System (ANFIS) implemented on an Arduino microcontroller to control a 5-degree-of-freedom robot arm. By combining MATLAB-based image processing with ANFIS, Komaro developed a dynamic model that enables the robot arm to accurately detect and interact with colored objects, showcasing a practical fusion of soft computing and real-time control. This contribution is significant for advancing autonomous robotic systems in manufacturing and sorting applications. Komaro’s work demonstrates a commitment to bridging theoretical fuzzy logic and neural networks with tangible robotic hardware, offering a scalable approach for low-cost, intelligent automation. With 26 citations, this paper has influenced subsequent research in adaptive control and computer vision for robotics, highlighting Komaro’s role in promoting accessible, efficient solutions for object detection and manipulation in dynamic environments.