A FPGA-Based Neuromorphic Locomotion System for Multi-Legged Robots

A FPGA-Based Neuromorphic Locomotion System for Multi-Legged Robots

The paper develops a neuromorphic system on a Spartan 6 field programmable gate array (FPGA) board to generate locomotion patterns (gaits) for three different legged robots (biped, quadruped, and hexapod). The neuromorphic system consists of a reconfigurable FPGA-based architecture for a 3G artifici...

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Bibliographic Details
Main Authors: Erick Israel Guerra-Hernandez, Andres Espinal, Patricia Batres-Mendoza, Carlos Hugo Garcia-Capulin, Rene De J. Romero-Troncoso, Horacio Rostro-Gonzalez
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
FPGA
spiking neural networks
neuromorphic engineering
legged robots
grammatical evolution
Victor-Purpura distance
Online Access:https://ieeexplore.ieee.org/document/7909022/
Description
Summary:The paper develops a neuromorphic system on a Spartan 6 field programmable gate array (FPGA) board to generate locomotion patterns (gaits) for three different legged robots (biped, quadruped, and hexapod). The neuromorphic system consists of a reconfigurable FPGA-based architecture for a 3G artificial neural network (spiking neural network), which acts as a Central Pattern Generator (CPG). The locomotion patterns, are then generated by the CPG through a general neural architecture, which parameters are offline estimated by means of grammatical evolution and Victor-Purpura distance-based fitness function. The neuromorphic system is fully validated on real biped, quadruped, and hexapod robots.
ISSN:2169-3536

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