Study of real-time biomimetic CPG on FPGA: behavior and evolution

• Main Authors: Timothée Levi, Yanchen Guo, Kazuyuki Aihara, Takashi Kohno
• Format: Article
• Language: English
• Published: Atlantis Press 2018-03-01
• Series: Journal of Robotics, Networking and Artificial Life (JRNAL)
• Subjects: Biomimetic neural network; CPG; FPGA; Silicon neuron
• Online Access: https://www.atlantis-press.com/article/25894376.pdf

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.