Koosuke Hattori
Papers
5
Total Citations
55
H-Index
4
About
Koosuke Hattori is a pioneering researcher in robot spatial language acquisition, whose work bridges robotics, linguistics, and artificial intelligence. His primary research areas include unsupervised lexical acquisition, place-name learning, and relative spatial concept formation for mobile robots. Hattori’s major contributions lie in developing methods that allow robots to learn the meaning of words from spoken utterances and sensorimotor data without prior linguistic knowledge. His most cited work, “Learning place-names from spoken utterances and localization results by mobile robot” (2011, 20 citations), introduced a novel approach for robots to autonomously associate place-names with their locations using only phoneme acoustic models. This foundational research has been extended in his later studies on relative spatial concepts, such as “Unsupervised lexical acquisition of relative spatial concepts using spoken user utterances” (2021, 7 citations), which enables robots to understand ambiguous spatial instructions like “left” or “near” through human-robot interaction. Hattori’s work has significantly advanced the field of human-robot communication, with cumulative citations exceeding 55, demonstrating its lasting impact on developing more intuitive and adaptive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Handy rangefinder for active robot vision18 citations · 2002
- 3Learning of Relative Spatial Concepts from ambiguous instructions8 citations · 2016
- 4
- 5