Iori Yanokura
Papers
16
Total Citations
62
H-Index
5
About
Iori Yanokura is a robotics researcher whose work bridges perception, manipulation, and human-robot interaction. His key research areas include robotic manipulation in cluttered environments, learning from observation, and applying foundation models to service robotics. Yanokura’s major contributions include developing a pick-and-verify system that dramatically improves picking reliability for objects in clutter—a critical advance for industrial automation. He also pioneered a simultaneous planning and estimation method based on physics reasoning, enabling robots to perform complex manipulation tasks like tool use. His work on semantic scene difference detection using pre-trained vision-language models allows mobile robots to patrol daily environments and identify changes, a key capability for domestic service robots. With multiple papers earning 8 citations each, Yanokura’s research has been recognized in venues like the Amazon Picking Challenge and RoboCup@Home. He also contributed to the WARABI Hand, a five-fingered robotic hand with flexible skin and force sensors designed for safe social interaction. His focus on integrating large-scale AI models with physical robotics positions him at the forefront of creating general-purpose service robots capable of understanding and acting in human environments.
Research Focus
Key Achievements
Top Papers
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- 5Verbal Focus-of-Attention System for Learning-from-Observation6 citations · 2021
- 6Verbal Focus-of-Attention System for Learning-from-Observation4 citations · 2020
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