Papers
104
Total Citations
2,659
H-Index
29
About
Katsu Yamane is a pioneering robotics researcher whose work spans humanoid robot dynamics, computational design optimization, human-robot interaction, and robotic manipulation. His early foundational contributions established efficient algorithms for computing the dynamics of structure-varying kinematic chains, work cited nearly 150 times, and helped advance the simulation of humanoid systems through the widely adopted OpenHRP platform. His 2005 study on somatosensory computation from motion-capture data, garnering over 200 citations, remains his most influential contribution, bridging biomechanical modeling and human-machine interfaces in a landmark way. Yamane further shaped humanoid robotics through sophisticated control frameworks enabling robots to simultaneously track motion-capture data and maintain balance. In later years, his research pivoted toward computational co-optimization of robot design and motion trajectories, producing multiple highly cited works that allow automated morphological design from high-level specifications. More recently, he has made notable strides in robotic fabric manipulation, applying deep imitation learning and visuospatial prediction to complex deformable object tasks with real-world applications in manufacturing and caregiving. With a cumulative citation record exceeding 1,000 across diverse subfields, Yamane's career exemplifies a remarkable breadth of rigorous, impactful contributions to modern robotics.
Research Focus
Key Achievements
Top Papers
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- 4Open architecture humanoid robotics platform97 citations · 2003
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- 73D printed soft skin for safe human-robot interaction84 citations · 2015
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- 9VisuoSpatial Foresight for Multi-Step, Multi-Task Fabric Manipulation71 citations · 2020
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