Study of real-time biomimetic CPG on FPGA: behavior and evolution
- 10.2991/jrnal.2018.4.4.9How to use a DOI?
- Biomimetic neural network, CPG, FPGA, Silicon neuron
Locomotion is one of the most basic abilities in animals. Neurobiologists have established that locomotion results from the activity of half-center oscillators that provides alternation of bursts. Central Pattern Generators (CPGs) are neural networks capable of producing rhythmic patterned outputs without rhythmic sensory or central input. We propose a network of several biomimetic CPGs using biomimetic neuron model and synaptic plasticity. This network is implemented on a FPGA (Field Programmable Gate Array). The network implementation architecture operates on a single computation core and in real-time. The real-time implementation of this CPGs network is validated by comparing it with biological data of leech heartbeat neural network. From these biomimetic CPGs, we use them for robotic applications and also for biomedical research to restore lost synaptic connections.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Timothée Levi AU - Yanchen Guo AU - Kazuyuki Aihara AU - Takashi Kohno PY - 2018 DA - 2018/03/31 TI - Study of real-time biomimetic CPG on FPGA: behavior and evolution JO - Journal of Robotics, Networking and Artificial Life SP - 299 EP - 302 VL - 4 IS - 4 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2018.4.4.9 DO - 10.2991/jrnal.2018.4.4.9 ID - Levi2018 ER -