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