Andrey Penkovskiy

Papers

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About

Andrey Penkovskiy is an emerging researcher specializing in robotic perception, simultaneous localization and mapping (SLAM), and autonomous navigation for mobile robotic systems. His work focuses on developing robust solutions that enable wheeled robots to operate reliably in challenging, real-world dynamic environments — a critical frontier in modern robotics research. Penkovskiy's most notable contribution is RVWO, a visual-wheel SLAM system that addresses one of the field's persistent challenges: maintaining accurate localization and mapping when environments contain moving objects and unpredictable elements. By integrating probabilistic frameworks with semantic prior information and visual re-projection error, RVWO demonstrates a sophisticated approach to sensor fusion that advances beyond traditional SLAM limitations. This work has garnered 7 citations since its 2023 publication, reflecting meaningful early traction within the research community. Complementing this, his work on optimizing sensor fusion and semantics for wheeled robots further refines bundle adjustment techniques through encoder measurement constraints, earning 4 citations. Together, these contributions position Penkovskiy as a focused voice in the growing conversation around perception-robust autonomous systems. Students exploring mobile robotics, sensor fusion, or dynamic environment navigation will find his research a valuable and practically grounded reference point.