Hiroshi YAMAURA

Tokyo Institute of Technology

Papers

8

Total Citations

43

H-Index

4

About

Hiroshi Yamaura is a pioneering researcher in the field of nonlinear dynamics and control of underactuated robotic systems, with a particular focus on achieving and stabilizing complex gymnastic motions. His major contributions center on the development and extension of chaos control techniques, most notably the **Multiple-prediction Delayed Feedback Control (MDFC)**, which he successfully applied to stabilize the giant swing motions of multi-link horizontal bar gymnastic robots. This work addresses the fundamental challenge of controlling systems with non-holonomic constraints, where traditional methods fall short. His most cited paper (2014, 12 citations) demonstrates the effectiveness of dynamic delayed feedback for a three-link robot, while his earlier studies (2011, 9 and 8 citations) established the theoretical foundation for MDFC with periodic gains. Beyond gymnastic robots, Yamaura has contributed to aerial posture control for acrobat robots, inverse kinematics for 6-DOF manipulators, and position control of linkage-based robotic fingers. His work on velocity and acceleration estimation using Radial Basis Function (RBF) interpolation also provides practical tools for motion control. With a career spanning foundational chaos control theory to experimental robotic implementations, Yamaura’s research offers critical insights for students and engineers working on the frontier of nonlinear control and bio-inspired robotic locomotion.

Research Focus

Key Achievements

4
H-Index
8
Papers
43
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Dynamic delayed feedback control for stabilizing the giant swing motions of an underactuated three-link gymnastic robot
12 citations · 2014
📈 Most Prolific Year: 2011 (3 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Tokyo Institute of Technology

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago