Oleg Shipitko

Institute for Information Transmission Problems

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About

Oleg Shipitko is a researcher at the intersection of robotics, computer vision, and computed tomography, whose work focuses on solving fundamental localization and estimation challenges. His primary research areas include indoor robot localization, visual edge detection, and tomographic imaging. Shipitko’s major contributions lie in developing precise positioning systems that fuse visual data with onboard motion sensors, as demonstrated in his most-cited work, "Edge detection based mobile robot indoor localization" (2019, 5 citations), which presents a robust method for estimating a mobile robot’s pose using building schematic plans. He has also pioneered novel approaches in microtomography with "TomoSLAM" (2022, 2 citations), where he applies factor graph optimization to refine rotation angles, addressing mechanical backlash and sensor errors in CT systems. His 2023 work on "Prior Distribution Refinement" (2 citations) introduces a method for generating accurate reference trajectories, enabling fairer evaluation of localization algorithms. Shipitko’s research is notable for bridging classical robotics techniques with advanced optimization methods, offering practical solutions for autonomous navigation and medical imaging. His work continues to influence both robotic perception and tomographic reconstruction communities.