In this work, the authors propose a combined approach based on a controller architecture that is able togenerate locomotion for a quadruped robot and a global optimization algorithm to generate head movementstabilization. The movement controllers are biologically inspired in the concept of Central Pattern Generators(CPGs) that are modelled based on nonlinear dynamical systems, coupled Hopf oscillators. This approachallows for explicitly specified parameters such as amplitude, offset and frequency of movement and to smoothlymodulate the generated oscillations according to changes in these parameters. The overall idea is to generatehead movement opposed to the one induced by locomotion, such that the head remains stabilized. Thus,in order to achieve this desired head movement, it is necessary to appropriately tune the CPG parameters.Three different global optimization algorithms search for this best set of parameters. In order to evaluatethe resulting head movement, a fitness function based on the Euclidean norm is investigated. Moreover, aconstraint-handling technique based on tournament selection was implemented.
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