Hiroki Fukada
Papers
1
Total Citations
1
H-Index
1
About
Hiroki Fukada is a robotics researcher whose work centers on the intersection of intelligent manipulation, deep learning, and real-time robotic control. His most notable contribution lies in developing a ROS2-based robotic system capable of handling granular food items with quantitative precision—a challenging task due to the irregular and deformable nature of such materials. By integrating a regression coefficient estimation-based deep learning model, Fukada’s approach enables robots to dynamically adjust grip and force in real time, achieving a level of dexterity previously difficult for automated food processing. Though his most-cited paper has garnered 1 citation to date, its novelty in applying deep regression techniques to physical manipulation marks a significant step toward more adaptive and safe human-robot interaction in agricultural and culinary settings. Fukada’s work is particularly relevant for researchers exploring soft robotics, sensor fusion, and the practical deployment of AI in unstructured environments. His focus on ROS2 ensures that his methods are immediately applicable to modern robotic platforms, bridging the gap between theoretical deep learning models and tangible, real-world automation.
Research Focus
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Top Papers
- 1