In autonomous robotics, the head shaking induced
by locomotion is a relevant and still not solved problem. This
problem constraints stable image acquisition and the possibility
to rely on that information to act accordingly.
In this article, we propose a movement controller to generate
locomotion and head movement. Our aim is to generate the
head movement required to minimize the head motion induced
by locomotion itself. The movement controllers are biologically
inspired in the concept of Central Pattern Generators (CPGs).
CPGs are modelled based on nonlinear dynamical systems,
coupled Hopf oscillators. This approach allows to explicitly
specify parameters such as amplitude, offset and frequency of
movement and to smoothly modulate the generated oscillations
according to changes in these parameters. Based on these
ideas, we propose a combined approach to generate head
movement stabilization on a quadruped robot, using CPGs and
an evolution strategy. The best set of parameters that generates
the head movement are computed by an evolution strategy.
Experiments were performed on a simulated AIBO robot.
The obtained results demonstrate the feasibility of the approach,
by reducing the overall head movement
