Soichiro Ikuno
Papers
4
Total Citations
30
H-Index
3
About
Soichiro Ikuno bridges the ancient and the cutting-edge, engineering humanoid robots that move with the grace of Japanese traditional puppetry. His core research lies at the intersection of affective robot motion design, human-robot interaction, and deep learning for robotics. Ikuno’s most influential work, “A deep learning framework for realistic robot motion generation” (2021, 20 citations), provides a foundational method for creating lifelike, data-driven movements. He is perhaps best known for his pioneering application of *Jo-ha-kyu*—the dramatic tempo structure from Bunraku puppet theater—to robot motion. By characterizing the 3D “squash and stretch” principles praised by UNESCO as “one of the most beautiful motions in the world,” Ikuno successfully implemented these expressive techniques in a life-size humanoid robot, demonstrating a novel path to overcoming the uncanny valley. His subsequent work (2024, 3 citations) tackles the challenge of robotic imitation without keyframes, using Multivariate Empirical Mode Decomposition to avoid jerky, unnatural movements. Through this unique synthesis of cultural aesthetics and computational methods, Ikuno is redefining what it means for a machine to move with emotional resonance and beauty.
Research Focus
Key Achievements
Top Papers
- 1A deep learning framework for realistic robot motion generation20 citations · 2021
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