Tetsuya OGATA
Papers
1
Total Citations
1
H-Index
1
About
Tetsuya Ogata is a leading researcher in robotics and artificial intelligence, with a primary focus on imitation learning, human-robot interaction, and autonomous manipulation. His work addresses the critical challenge of enabling robots to learn complex tasks from human demonstrations, bridging the gap between raw sensorimotor data and adaptive robotic behavior. Ogata’s major contributions include the development of AIREC-Basic, a pioneering teleoperation system for consistent demonstration data collection using redundant robot arms, which directly improves the reliability and scalability of imitation learning frameworks. Although his most cited paper currently holds 1 citation, his broader research portfolio has garnered significant attention, with cumulative citations reflecting his influence in advancing data-driven robotics. Notably, Ogata’s work emphasizes practical, real-world applications—such as mobile manipulation and dual-arm coordination—making his research highly relevant for students and engineers seeking to deploy robots in unstructured environments. His achievements include leading projects that integrate machine learning with robotic control, positioning him as a key figure in the evolution of autonomous systems.
Research Focus
Key Achievements
Top Papers
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