Testing the Effects of Evolved Central Pattern Generators in an Articulated Robot Animat Ecosystem

This study added central pattern generators (CPGs) to 3D artificial animal (i.e., animat)articulated robots contained in a simulated ecosystem. Specifically, Hopf and Matsuoka CPG equations were added to the hidden neuron calculations, and the effects of these augmentations on robot behavior were analyzed. The results indicated that robots utilizing sum-and-squash neurons with the CPG equations in the hidden neuron equation performed better than robots using only sum-and-squash neurons without CPGs. The rhythmic motor patterns generated by the CPG dynamics helped the articulated robots to move around the environment, as well as to better accomplish survival and reproduction. The robots equipped with CPGs were able to reproduce more often and with higher energy efficiency than the No CPG robots. The performance advantage in birthrates of robots with CPGs over robots without CPGs increased as the simulation progressed. Overall, the addition of CPGs to the neurons of 3D articulated robots provided useful rhythmic movement that proved beneficial for movement, survival, and reproduction.