Y. Furuta
Papers
6
Total Citations
80
H-Index
6
About
Y. Furuta is a roboticist whose work sits at the intersection of cloud robotics, semantic navigation, and autonomous learning. Their most impactful research, "The Exchange of Knowledge Using Cloud Robotics" (2018, 40 citations), tackles a fundamental challenge in robotics: enabling machines to flexibly perform human-level tasks by sharing knowledge through cloud-based systems. This crowd-sourcing approach addresses the "knowledge gap problem" that limits individual robots operating in varying conditions. Furuta further advanced autonomous navigation with their work on transformable semantic maps (2016), which uses deep learning object segmentation to help assistive robots navigate dynamic home environments without relying on rigid geometric representations. Their research on continuous modeling of affordances in symbolic knowledge bases (2019) explores how robots can improve manipulation skills over time, mirroring human learning. Notably, Furuta contributed to Team NEDO-JSK's participation in the DARPA Robotics Challenge (2015), developing a humanoid integrated UI system for supervised autonomy under unreliable network conditions—a practical demonstration of their expertise in real-world robotic deployment. With additional work on long-term episodic memory for maintaining local rules in home environments, Furuta continues to push toward robots that truly understand and adapt to human spaces.
Research Focus
Key Achievements
Top Papers
- 1The Exchange of Knowledge Using Cloud Robotics40 citations · 2018
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- 3The Exchange of Knowledge Using Cloud Robotics9 citations · 2018
- 4Continuous Modeling of Affordances in a Symbolic Knowledge Base8 citations · 2019
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