Ryunosuke Yamada
Papers
2
Total Citations
4
H-Index
1
About
Ryunosuke Yamada is a robotics researcher whose work bridges computational geometry and practical automation, with a focus on enabling robots to handle complex physical interactions. His key research areas include robot motion planning, collision detection, and the manipulation of flexible materials. Yamada’s major contribution is a fast and precise method for approximating the Minkowski sum of two rotational ellipsoids with a superellipsoid, a fundamental operation in applications like robot path planning and particle flow simulation. This work, published in 2024, has already garnered 3 citations, highlighting its immediate relevance to the field. Additionally, Yamada has tackled the challenging problem of adhesive dispensing, a task where robots must manage unpredictable, flexible materials. He proposed both analysis-based and learning-based models to predict adhesive behavior during dispensing, enabling more reliable trajectory generation for manufacturing robots. This dual approach—combining theoretical modeling with data-driven learning—demonstrates his versatility in addressing real-world robotic challenges. Yamada’s research is notable for its direct applicability to industrial automation, offering practical solutions that improve robot precision and adaptability in tasks involving deformable objects.
Research Focus
Key Achievements
Top Papers
- 1
- 2