Masahiro Sekimoto
Papers
31
Total Citations
478
H-Index
11
About
Masahiro Sekimoto is a robotics researcher whose work centers on the control of kinematically redundant robotic systems, human-like motion generation, and the mathematical foundations of manipulation and grasping. He is best known for tackling the longstanding "Bernstein problem" — the challenge of how biological and robotic systems resolve the ill-posedness of inverse kinematics when degrees of freedom exceed task requirements. His landmark 2005 paper (122 citations) proposed a natural resolution to this problem without relying on artificial performance indices, offering a biologically inspired perspective that reshaped thinking in both robotics and motor control. Building on this, his "virtual spring-damper hypothesis," introduced in 2006 (75 citations), provided an elegant, physically intuitive control framework for human-like multi-joint reaching movements. Sekimoto further advanced the field through differential-geometric and Riemannian-geometry approaches for motion planning and constrained manipulation, enabling more principled control of complex robotic arm-finger systems. His contributions to iterative learning control for redundant robots have also strengthened the bridge between theoretical rigor and practical implementation. Collectively, his body of work has earned over 370 citations, making him a notable voice in biomimetic robotics and advanced motion control research.
Research Focus
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