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About

Sherzod Turaev is a robotics and automation researcher whose work centers on intelligent navigation, autonomous inspection, and sensor-driven control systems. His primary contributions lie in mobile robot path planning and real-world industrial inspection, where he has developed novel algorithms that enable robots to operate safely in constrained and dynamic environments. Turaev’s most influential work introduces the Generalized Laser Simulator (GLS) algorithm, a path-planning method that allows wheeled mobile robots to navigate two-dimensional maps while avoiding static and dynamic obstacles. This algorithm, detailed in his 2021 and 2022 papers, has garnered over 26 combined citations for its practical approach to obstacle avoidance and target identification. In a notable applied achievement, Turaev led the development of an automatic visual inspection system for oil tank exteriors using unmanned aerial vehicles (UAVs) paired with cascading fuzzy logic and image processing. This 2023 work, cited 15 times, addresses critical corrosion detection challenges in the oil and gas industry, enhancing safety and reducing manual inspection risks. His more recent 2025 research on sensor fusion for mobile robot localization in road-following and roundabout environments further demonstrates his commitment to advancing autonomous navigation in complex, real-world settings. Turaev’s work bridges theoretical algorithm design with practical deployment, making him a valuable contributor to the fields of robotics, computer vision, and industrial automation.