Papers
8
Total Citations
77
H-Index
4
About
Ryusuke Sagawa is a leading researcher in robotics and computer vision, whose work bridges the gap between perception, modeling, and autonomous motion. His key research areas include 3D environment reconstruction, stereovision systems, and human-robot interaction, with a particular focus on enabling robots to perceive and move with human-like dexterity and expressivity. Sagawa’s major contributions span from foundational work in catadioptric stereovision—where he pioneered methods for single-camera, multi-mirror systems for mobile robot navigation—to cutting-edge advances in inverse kinematics and generative motion modeling. His 2006 paper on stereovision quality estimation has garnered 34 citations, while his recent 2023 work on fast inverse kinematics for musculoskeletal models and his 2024 generative model for embedding human expressivity into robot motions each have 12 citations, reflecting growing impact. Notably, Sagawa has also developed hierarchical reinforcement learning frameworks for quadrupedal locomotion and manipulator reactive motion, and applied calibration-free 3D scanning to robotic surgery. His work on visibility reduction for safety sensors further demonstrates his commitment to real-world robotic deployment. Through these diverse contributions, Sagawa is shaping the future of autonomous systems that move and interact with human-like sophistication.
Research Focus
Key Achievements
Top Papers
- 1Stereovision with a Single Camera and Multiple Mirrors34 citations · 2006
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- 3A Generative Model to Embed Human Expressivity into Robot Motions12 citations · 2024
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