Riku Tazawa
Papers
2
Total Citations
17
H-Index
2
About
Riku Tazawa is a researcher in bio-inspired robotics, focusing on the neural control of locomotion in quadruped robots. His work centers on non-programmed gait generation, drawing inspiration from the spinal neural networks—central pattern generators—that enable animals to walk without conscious effort. Tazawa’s major contribution is the development of pulse-type hardware neuron models that mimic biological neurons, allowing robots to autonomously generate adaptive gaits without pre-programmed instructions. His 2020 paper, “Non-programmed gait generation of quadruped robot using pulse-type hardware neuron models,” has garnered 12 citations, establishing a foundation for energy-efficient, self-organizing robotic locomotion. Building on this, his 2022 study, “Dynamic simulation of non-programmed gait generation of quadruped robot,” with 5 citations, validated these principles through simulation, demonstrating how neural dynamics can produce stable, versatile gaits in virtual environments. Tazawa’s work bridges computational neuroscience and robotics, offering a pathway toward more autonomous, animal-like machines. His research is particularly notable for its potential to reduce the need for explicit programming in robotic control, a step toward truly adaptive systems. For students and researchers, Tazawa’s contributions illuminate how biological principles can revolutionize robot design.
Research Focus
Key Achievements
Top Papers
- 1
- 2Dynamic simulation of non-programmed gait generation of quadruped robot5 citations · 2022