Ramil Mukhametshin
Papers
1
Total Citations
9
H-Index
1
About
Ramil Mukhametshin is a robotics researcher whose work centers on the intersection of computer vision, trajectory estimation, and autonomous manipulation. His most-cited paper, "Transportation of small objects by robotic throwing and catching: applying genetic programming for trajectory estimation" (2018, 9 citations), introduces a novel algorithm that uses genetic programming to predict the future path of a thrown object from dual-camera video input. This contribution addresses a core challenge in dynamic robotic tasks—enabling a robot to track, forecast, and catch moving objects with improved accuracy. By combining evolutionary computation with real-time visual tracking, Mukhametshin’s approach offers a computationally efficient alternative to traditional filtering methods, advancing the field of robotic dexterity and object transportation. His work has practical implications for automated logistics, manufacturing, and human-robot collaboration, where precise catching and throwing can streamline material handling. Though early in his career, Mukhametshin’s research demonstrates a clear focus on bridging perception and action in robotics, laying groundwork for more adaptive and agile autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1