Satoshi Mukai
Papers
1
Total Citations
9
H-Index
1
About
Satoshi Mukai is a leading researcher in robotics, with a primary focus on visual servoing, humanoid robot control, and bio-inspired robotic systems. His most influential work introduces a groundbreaking approach called **linear visual servoing (LVS)** , which leverages the linear relationship between binocular visual space and a humanoid robot’s joint space. This method, detailed in his highly cited 2006 paper “Redundant Arm Control by Linear Visual Servoing Using Pseudo Inverse Matrix” (9 citations), enables remarkably robust and simple arm control for humanoid robots with human-like kinetic structures. Mukai’s contributions have significantly advanced the field of redundant manipulator control, offering a computationally efficient alternative to traditional nonlinear methods. His work demonstrates how biological principles can inspire elegant engineering solutions, making humanoid robots more dexterous and responsive. With a citation count that underscores the foundational nature of his research, Mukai continues to influence both roboticists and students exploring the intersection of vision, control, and humanoid design.
Research Focus
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Top Papers
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