Hiroaki Kudo
Papers
2
Total Citations
10
H-Index
2
About
Hiroaki Kudo’s research lies at the intersection of human-robot interaction and multimodal perception, focusing on how robots can understand and respond to natural human cues. His most-cited work, “Informing a Robot of Object Location with Both Hand-Gesture and Verbal Cues” (2003, 6 citations), pioneered an interface that combines gesture and speech for object localization—a foundational step toward intuitive robot communication in human living spaces. This work addresses a critical challenge in domestic robotics: enabling seamless, natural instruction without specialized training. Kudo further advanced sensor integration in “Finding the Correspondence of Audio-Visual Events by Object Manipulation” (2008, 4 citations), where he proposed a method for robots to actively manipulate objects to learn correspondences between sound and sight, mirroring human sensory integration. This active learning approach highlights his broader contribution to embodied cognition in robotics. Though his citation counts are modest, Kudo’s work is notable for its early recognition of the importance of multimodal, active perception in human-robot interaction—a theme now central to modern robotics. His research offers valuable insights for students exploring how robots can perceive and interact with the world as humans do.
Research Focus
Key Achievements
Top Papers
- 1
- 2Finding the Correspondence of Audio-Visual Events by Object Manipulation4 citations · 2008