Megumi Aibara
Papers
2
Total Citations
10
H-Index
2
About
Megumi Aibara is a researcher at the forefront of bio-inspired robotics, specializing in the development of low-power, biologically plausible control systems for robotic motion. Her work focuses on creating pulse-type hardware neural networks that mimic the function of the spinal cord, enabling efficient and adaptive locomotion in robots. Aibara's major contribution lies in demonstrating how a hardware-based central pattern generator (CPG) model can control walking and running in a human musculoskeletal robot, achieving motion control with remarkably low energy consumption—a critical challenge in modern robotics. Her most-cited paper (2022, 6 citations) showcases this approach, while her earlier work (2021, 4 citations) established the foundational neural network architecture. By drawing inspiration from living organisms, Aibara's research bridges neuroscience and engineering, offering a pathway toward more autonomous, efficient, and lifelike robotic systems. Her work is particularly notable for its potential to reduce the computational and power demands of motion control, making it highly relevant for applications in prosthetics, exoskeletons, and field robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Pulse-type hardware neural network mimicking spinal cord function4 citations · 2021