Akihiro Miki
Papers
10
Total Citations
54
H-Index
4
About
Akihiro Miki is a robotics researcher pushing the boundaries of how machines interact with the physical world, focusing on three key areas: dynamic manipulation of flexible objects, high-performance legged locomotion, and musculoskeletal robot design. His most impactful work introduces a deep predictive model with parametric bias for dynamic cloth manipulation, addressing the long-standing challenge of handling deformable materials—a paper that has garnered 15 citations. Miki also leads the development of RAMIEL, a parallel-wire driven monopedal robot capable of continuous high jumps, demonstrating novel approaches to legged locomotion in three-dimensional environments. His contributions to musculoskeletal robotics include adaptive body schema learning for robots with additional muscles and the hardware-software architecture of the wheeled robot Musashi-W, which bridges the gap between flexible humanoid design and real-world applications. More recently, Miki has explored self-healing systems using liquid metal sloshing for high-load tendon-driven robots, achieving tensile strength recovery over 1kN. His work on DIJE (Dense Image Jacobian Estimation) advances robust visual servoing, while his patterned structure muscle concept enables arbitrary-shaped wire-driven artificial muscles. With over 50 citations across his publications, Miki’s research is shaping the future of adaptive, resilient, and highly capable robotic systems.
Research Focus
Key Achievements
Top Papers
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