Kousuke Mano
Papers
1
Total Citations
3
H-Index
1
About
Kousuke Mano is a researcher in robotics and computer vision, with a primary focus on advancing object manipulation for industrial applications. His key research areas include grasp planning, robotic perception, and real-time object interaction. Mano’s major contribution is the development of Fast Graspability Evaluation (FGE), a method that uses eigenvalue templates to rapidly and precisely detect optimal grasping positions on objects. This approach employs convolution of hand templates with object regions, enabling industrial robots to estimate the best grasping posture with high speed and accuracy. While his most-cited work, "Fast and Precise Detection of Object Grasping Positions with Eigenvalue Templates" (2019), has garnered 3 citations, its practical impact is notable for addressing the critical challenge of real-time grasp detection in manufacturing settings. Mano’s research bridges the gap between theoretical computer vision and applied robotics, offering efficient solutions for automation. His work is particularly valuable for students and researchers interested in robotic manipulation, template-based perception, and the integration of fast algorithms into industrial systems, highlighting a commitment to enhancing robot autonomy and operational efficiency.
Research Focus
Key Achievements
Top Papers
- 1