Mikihito Hayakawa
Papers
2
Total Citations
10
H-Index
2
About
Mikihito Hayakawa is a researcher at the forefront of bio-inspired robotics, specializing in the development of low-power, biologically plausible control systems for robotic motion. His key research areas include central pattern generators (CPGs), pulse-type hardware neural networks, and musculoskeletal robotic control. Hayakawa’s major contribution lies in designing hardware neural networks that mimic the function of the spinal cord, enabling efficient walking and running in human-like musculoskeletal models. His most-cited work, “The walking and running control of a human musculoskeletal model using a low-power consumption hardware central pattern generator model” (2022, 6 citations), demonstrates a novel approach to achieving energy-efficient, low-load motion control—a critical challenge in robotics. Building on this, his 2021 paper on pulse-type hardware neural networks further explores spinal cord emulation. Though his citation counts are modest, Hayakawa’s work is notable for its potential to revolutionize prosthetics, exoskeletons, and autonomous robots by bridging neuroscience and engineering. His research offers a promising path toward robots that move with the fluidity and efficiency of living organisms.
Research Focus
Key Achievements
Top Papers
- 1
- 2Pulse-type hardware neural network mimicking spinal cord function4 citations · 2021