Shaban Usman

University of Electronic Science and Technology of China

Papers

Total Citations

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About

Shaban Usman is a researcher at the forefront of intelligent robotics and manufacturing optimization, whose work bridges adaptive control systems and artificial intelligence. His primary research focuses on autonomous mobile robot navigation in cluttered and unknown environments, where he has pioneered the use of hybrid adaptive neuro-fuzzy inference systems (ANFIS) integrated with sensor fusion. His most-cited paper (2022, 37 citations) introduces a robust framework for collision-free navigation that overcomes the limitations of prior methods—namely poor performance in complex settings and high computational costs—by combining fuzzy logic with neural network adaptability. This work, alongside a related study on autonomous navigation (6 citations), demonstrates his ability to tackle real-world challenges in robotics, such as processing uncertainty and dynamic obstacles. Beyond robotics, Usman has explored AI-integrated approaches for job-shop scheduling with resource flexibility (2026), signaling a growing impact on smart manufacturing. His contributions are particularly notable for their practical applicability, offering scalable solutions for autonomous systems in logistics, industrial automation, and service robotics. With a trajectory that marries theoretical rigor with engineering innovation, Usman is shaping the next generation of intelligent, adaptive machines.