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About

Mustafa Engin is a researcher whose work sits at the intersection of embedded systems, robotics, and control engineering. His primary contributions focus on developing intelligent, energy-efficient controllers for autonomous mobile robots, with applications ranging from industrial service tasks to renewable energy. Engin’s most cited work, "Path planning of line follower robot" (56 citations), established a foundation for precise, ARM Cortex-based navigation. He further advanced the field with an "Embedded LQR controller design for self-balancing robot" (11 citations), demonstrating how velocity feedback alone can stabilize a two-wheeled robot. His recent foray into machine learning for service robots (2023, 7 citations) signals a shift toward adaptive, AI-driven automation. Engin also addresses critical hardware constraints in "Energy Efficiency of Embedded Controllers" (6 citations), a vital concern for battery-powered devices. His practical, hands-on approach is evident in case studies like the "fire fighting robot" (5 citations), which serves as an educational tool for real-time system design. With a cumulative impact of nearly 100 citations, Engin’s work bridges theoretical control theory with tangible, low-cost embedded solutions, making him a notable figure in the development of smarter, more efficient autonomous systems.