Papers

6

Total Citations

46

H-Index

5

About

Yuki Inoue’s research spans the frontiers of embodied intelligence, bio-inspired robotics, and human–machine symbiosis, with a focus on translating complex control theories into real-world robotic systems. Inoue made a significant contribution to embodied instruction following (EIF) with the “Prompter” framework, which leverages large language model prompting to enable data-efficient, long-horizon task execution for mobile manipulation robots—a critical step toward deploying autonomous agents beyond simulation. This work has garnered 15 citations and underscores Inoue’s commitment to bridging language and physical action. In parallel, Inoue has advanced snake-like robot locomotion, deriving optimal swimming gaits in viscous fluids (10 citations), and pioneered clinically viable myoelectric prosthetic hands with multi-degree-of-freedom control, achieving 6 citations for a study on long-term outcomes that pushes toward practical “cyborg” applications. Earlier foundational work includes impedance control for golf swing robots to emulate different-arm-mass golfers and synchronous imitation control for biped robots using wearable motion analysis, both published in 2008. Inoue’s career reflects a rare ability to integrate control theory, biomechanics, and AI, producing innovations that are as theoretically rigorous as they are practically transformative.

Research Focus

Key Achievements

5
H-Index
6
Papers
46
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Prompter: Utilizing Large Language Model Prompting for a Data Efficient Embodied Instruction Following
15 citations · 2022
📈 Most Prolific Year: 2008 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Osaka Metropolitan University, University of Electro-Communications, Kochi University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago