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Computational Intelligence and Neuroscience
Volume 2016, Article ID 5615618, 13 pages
Research Article

Quadrupedal Robot Locomotion: A Biologically Inspired Approach and Its Hardware Implementation

1Division of Postgraduate Studies and Research, Leon Institute of Technology, 37290 Leon, GTO, Mexico
2Department of Electronics, DICIS, University of Guanajuato, 36885 Salamanca, GTO, Mexico
3Department of Organizational Studies, DCEA, University of Guanajuato, 36250 Guanajuato, GTO, Mexico
4Division of Postgraduate Studies and Research, Tijuana Institute of Technology, 22414 Tijuana, BC, Mexico

Received 12 February 2016; Revised 6 April 2016; Accepted 24 May 2016

Academic Editor: Ricardo Aler

Copyright © 2016 A. Espinal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A bioinspired locomotion system for a quadruped robot is presented. Locomotion is achieved by a spiking neural network (SNN) that acts as a Central Pattern Generator (CPG) producing different locomotion patterns represented by their raster plots. To generate these patterns, the SNN is configured with specific parameters (synaptic weights and topologies), which were estimated by a metaheuristic method based on Christiansen Grammar Evolution (CGE). The system has been implemented and validated on two robot platforms; firstly, we tested our system on a quadruped robot and, secondly, on a hexapod one. In this last one, we simulated the case where two legs of the hexapod were amputated and its locomotion mechanism has been changed. For the quadruped robot, the control is performed by the spiking neural network implemented on an Arduino board with 35% of resource usage. In the hexapod robot, we used Spartan 6 FPGA board with only 3% of resource usage. Numerical results show the effectiveness of the proposed system in both cases.