Yohei Ohata
Papers
2
Total Citations
11
H-Index
2
About
Yohei Ohata is a pioneering researcher in biologically inspired robotics, specializing in adaptive motor control through cerebellar neuronal network models. His work bridges computational neuroscience and robotics, focusing on how the cerebellum’s structure can inform stable, real-time control systems. Ohata’s major contribution lies in developing adaptive controllers for two-wheeled balancing robots, where he integrated feedback (PD) controllers with cerebellar models to achieve robust, learning-based stabilization. His 2010 paper, with 9 citations, demonstrated this approach in both simulation and real-world environments, marking a significant step in applying neural circuitry to physical systems. A subsequent 2012 study expanded this framework to a two-hemispheric cerebellar model, exploring bilateral motor learning and cognitive processing. Though his citation counts are modest, Ohata’s work is notable for its direct translation of cerebellar learning mechanisms—such as synaptic plasticity and sensory-motor integration—into functional robotic control. This research offers valuable insights for students and researchers in neurorobotics, adaptive control, and computational neuroscience, highlighting how biological principles can solve engineering challenges in dynamic balance and motor coordination.
Research Focus
Key Achievements
Top Papers
- 1
- 2