Papers
50
Total Citations
881
H-Index
16
About
Ko Ayusawa is a prominent robotics researcher whose work sits at the intersection of humanoid robotics, biomechanics, and multibody system dynamics. Best known for his foundational contributions to inertial parameter identification, Ayusawa has developed mathematically rigorous methods for estimating the dynamic properties of legged systems — including humanoid robots and humans — that do not rely on a fixed base, addressing a critical challenge in real-world robotics applications. His 2013 paper on identifiability using underactuated base-link dynamics has garnered over 113 citations and remains a landmark reference in the field. Beyond parameter identification, Ayusawa has made significant strides in motion retargeting, enabling seamless translation of human motion onto humanoid platforms through simultaneous morphing and optimization techniques (77 citations), and in hierarchical optimization strategies for inertia estimation (76 citations). His work extends into joint torque sensing, deformable object manipulation, and wearable assistive robotics for lumbar support, reflecting a remarkably broad research vision. His development of persistently exciting trajectory generation methods further underscores his commitment to rigorous, practical identification frameworks. With a body of work spanning simulation, hardware, and theory, Ayusawa has established himself as a versatile and impactful figure in modern robotics research.
Research Focus
Key Achievements
Top Papers
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- 7Simulation-based optimal motion planning for deformable object36 citations · 2015
- 8Standard Performance Test of Wearable Robots for Lumbar Support30 citations · 2018
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