About

Shunsuke Kudoh is a robotics researcher whose work spans humanoid locomotion, dexterous manipulation, and robot learning, with a particular focus on enabling robots to perform complex, human-like tasks with intelligence and adaptability. His most impactful contribution — a feedback controller allowing biped humanoids to counteract large perturbations during gait (96 citations) — addressed a fundamental challenge in bipedal stability by leveraging angular momentum compensation, a critical step toward robust real-world humanoid deployment. Alongside this, his work on motion generation with physical constraints (35 citations) demonstrated how human-recorded motion could be intelligently adapted for robotic execution. Kudoh has also made notable strides in robot dexterity, pioneering in-air rope knotting with dual-arm multi-finger systems and developing food peeling and precision pouring methods that push service robots toward practical domestic applications. His learning-from-observation paradigm, formalized through Labanotation-based motion description (33 citations), offers a principled framework for robots to acquire skills by watching humans. Perhaps most creatively, his work on music-responsive dancing robots demonstrates an impressive integration of perception, motion planning, and real-time adaptability. Collectively, his research reflects a sustained commitment to bridging human capability and robotic performance across diverse, everyday scenarios.

Research Focus

Key Achievements

13
H-Index
43
Papers
560
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
A Feedback Controller for Biped Humanoids that Can Counteract Large Perturbations During Gait
96 citations · 2006
📈 Most Prolific Year: 2012 (7 Papers)
🤝 Key Collaborators: 54
🏛 Institutions: The University of Tokyo, University of Electro-Communications, Induk University, Tokyo University of Science, Graduate School USA

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago