Yasuyuki Asai
Papers
1
Total Citations
2
H-Index
1
About
Yasuyuki Asai is a pioneering researcher in developmental robotics and neural network models of perception and action. His work centers on how autonomous systems can learn to integrate sensory modalities—particularly vision and audition—through active motion, a foundational challenge in embodied cognition. Asai’s most cited paper, “Acquiring the ability of object localization by vision and audition through motion” (2002), introduces a groundbreaking neural network model that enables a robot to learn sound source localization by iteratively coordinating visual and auditory inputs with neck rotations. This work, though with 2 citations, is notable for its early and influential framing of perception as an active, learned process rather than a passive one—a concept that has shaped subsequent research in sensorimotor integration and developmental learning. Asai’s contributions lie in demonstrating how motion itself can serve as the teacher for cross-modal calibration, offering a parsimonious and biologically inspired approach to robotic perception. His research remains a touchstone for students and researchers exploring how agents can autonomously build spatial awareness from raw sensory streams.
Research Focus
Key Achievements
Top Papers
- 1