Sergey Gladilin
Papers
1
Total Citations
3
H-Index
1
About
Sergey Gladilin is a robotics researcher specializing in visual localization and perception for unmanned systems. His key research areas include stereo vision, 3D reconstruction, and autonomous navigation. Gladilin's most notable contribution is a novel approach to stereo-based visual localization that eliminates the need for traditional triangulation. In his 2017 paper, he proposed a method that minimizes the sum of squared distances between 3D points and corresponding 3D rays, enabling robust pose estimation directly from stereo image pairs. This technique demonstrates strong practical performance for real-world localization tasks, showing particular resilience to measurement noise and outliers. While his citation count remains modest, the work represents a meaningful step toward efficient, geometrically principled localization for robotics platforms. Gladilin's research addresses a fundamental challenge in autonomous navigation: achieving accurate position estimation without heavy computational overhead. His approach offers advantages for applications where speed and robustness are critical, such as unmanned ground vehicles operating in GPS-denied environments. The work continues to inform developments in visual odometry and simultaneous localization and mapping (SLAM) systems.
Research Focus
Key Achievements
Top Papers
- 1