  In a developmental framework, autonomous robots need to explore the world and
learn how to interact with it. Without an a priori model of the system, this
opens the challenging problem of having robots master their interface with the
world: how to perceive their environment using their sensors, and how to act in
it using their motors. The sensorimotor approach of perception claims that a
naive agent can learn to master this interface by capturing regularities in the
way its actions transform its sensory inputs. In this paper, we apply such an
approach to the discovery and mastery of the visual field associated with a
visual sensor. A computational model is formalized and applied to a simulated
system to illustrate the approach.
