Yoshi Ri
Papers
1
Total Citations
9
H-Index
1
About
Yoshi Ri is a researcher in robotics and computer vision, with a focus on motion estimation and visual servoing. His work addresses the challenge of reconstructing precise camera motion from video sequences, a critical capability for autonomous robot guidance and task learning. In his most cited paper, "Drift-free motion estimation from video images using phase correlation and linear optimization" (2018, 9 citations), Ri introduced a novel approach that combines phase correlation with linear optimization to achieve drift-free motion reconstruction. This method enhances the accuracy and stability of image-based visual servoing, enabling robots to reliably interpret and replicate movements from visual data. By tackling the cumulative errors that plague traditional motion estimation techniques, Ri’s contribution supports more robust autonomous navigation and skill transfer in robotics. His work is particularly valuable for researchers developing vision-driven robotic systems, offering a practical solution for real-time, high-precision motion tracking from standard video inputs.
Research Focus
Key Achievements
Top Papers
- 1