Sergey Zagoruyko
Papers
2
Total Citations
80
H-Index
2
About
Sergey Zagoruyko is a leading researcher in computer vision and robotics, best known for his pioneering work on visually guided rearrangement planning. His key research areas include Monte-Carlo tree search, robotic manipulation, and visual perception for autonomous systems. Zagoruyko’s major contribution is the development of a complete pipeline that leverages Monte-Carlo tree search to efficiently plan sequences of actions for moving multiple objects from an initial arrangement to a desired configuration, relying solely on RGB camera inputs. This work, detailed in his most-cited paper (2019, 73 citations), addresses the challenging problem of visually guided rearrangement with many movable objects, bridging the gap between high-level planning and low-level visual feedback. His follow-up study (2020, 7 citations) further refines this approach, demonstrating its robustness in real-world scenarios. Zagoruyko’s research has significant implications for warehouse automation, domestic robotics, and assistive technologies, enabling robots to perform complex tasks in cluttered environments. His innovative integration of Monte-Carlo tree search with visual perception has established him as a key figure in advancing intelligent robotic systems, inspiring future work in efficient, visually guided decision-making.
Research Focus
Key Achievements
Top Papers
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