Tadashi Hashimoto
Papers
1
Total Citations
132
H-Index
1
About
Tadashi Hashimoto is a pioneering researcher in robotics and machine learning, best known for his groundbreaking work on robotic table tennis. His most-cited paper, "A learning approach to robotic table tennis" (2005, 132 citations), introduced a novel method for controlling a robot to return an incoming ball to a desired target with precise flight duration. By employing locally weighted regression to model three key input-output maps—ball prediction, racket control, and trajectory planning—Hashimoto demonstrated how robots can learn complex, real-time motor skills through data-driven approaches. This work has had a lasting impact on the fields of robot learning and dynamic motion control, influencing subsequent research in adaptive robotics and sensorimotor systems. Hashimoto’s contributions highlight the power of combining machine learning with physical interaction, offering a compelling example of how robots can achieve human-like dexterity in fast-paced environments. His research continues to inspire students and engineers working at the intersection of artificial intelligence and robotics, showcasing the potential for machines to master tasks that require both perception and precise action.
Research Focus
Key Achievements
Top Papers
- 1A learning approach to robotic table tennis132 citations · 2005