Igor Kyrychenko

Kharkiv National Automobile and Highway University

Papers

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About

Igor Kyrychenko is a robotics researcher whose work focuses on advancing autonomous control systems for heavy machinery, particularly robotic excavators. His key research areas include stochastic control theory, trajectory tracking, and the application of optimal control methods to construction and mining equipment. Kyrychenko's most notable contribution is his development of a Linear Quadratic Gaussian (LQG) control framework for robotic excavators, addressing the critical challenge of precise trajectory tracking in the presence of system disturbances and measurement noise. By modeling these uncertainties as stochastic white noise processes, his approach provides a mathematically rigorous solution to a practical problem that has long hindered the deployment of autonomous excavators in real-world environments. While his work has accumulated 2 citations to date, its significance lies in bridging the gap between classical control theory and field robotics. This research has direct implications for improving efficiency and safety in construction and mining operations, where precise manipulation under uncertain conditions is essential. Kyrychenko's work represents an important step toward fully autonomous heavy equipment, demonstrating how sophisticated control strategies can be adapted for challenging real-world applications.