  The challenge of robotic reproduction -- making of new robots by recombining
two existing ones -- has been recently cracked and physically evolving robot
systems have come within reach. Here we address the next big hurdle: producing
an adequate brain for a newborn robot. In particular, we address the task of
targeted locomotion which is arguably a fundamental skill in any practical
implementation. We introduce a controller architecture and a generic learning
method to allow a modular robot with an arbitrary shape to learn to walk
towards a target and follow this target if it moves. Our approach is validated
on three robots, a spider, a gecko, and their offspring, in three real-world
scenarios.
