Yuichi Tazaki
Kobe University, Tokyo Institute of Technology, Nagoya University
Papers
26
Total Citations
224
H-Index
7
About
Yuichi Tazaki is a leading researcher in the field of legged and humanoid robotics, with a primary focus on model predictive control (MPC), motion planning, and teleoperation. His most influential work, “Model predictive control of legged and humanoid robots: models and algorithms” (2023, 76 citations), provides a comprehensive framework that has become a cornerstone for modern locomotion control. Tazaki’s contributions extend to practical applications, such as the comparative study of manipulator teleoperation for nuclear decommissioning at Fukushima Daiichi (30 citations), demonstrating his commitment to solving real-world challenges. He pioneered the Graph-Based Model Predictive Control method for bipedal robots (17 citations) and developed a closed-form solution of centroidal dynamics for versatile motion generation (2024, 8 citations). His survey on motion planning for humanoid robots (14 citations) serves as a key reference for new researchers. Tazaki’s work also explores energy-efficient passive dynamic walking and haptic feedback for material discrimination, showcasing his breadth. With over 170 total citations, his research has significantly advanced both theoretical foundations and practical implementations in humanoid locomotion and control.
Research Focus
Key Achievements
Top Papers
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- 3Graph Based Model Predictive Control of a Planar Bipedal Robot17 citations · 2006
- 4A survey of motion planning techniques for humanoid robots14 citations · 2020
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