  Evolution and development operate at different timescales; generations for
the one, a lifetime for the other. These two processes, the basis of much of
life on earth, interact in many non-trivial ways, but their temporal hierarchy
-- evolution overarching development -- is observed for most multicellular
lifeforms. When designing robots however, this tenet lifts: it becomes --
however natural -- a design choice. We propose to inverse this temporal
hierarchy and design a developmental process happening at the phylogenetic
timescale. Over a classic evolutionary search aimed at finding good gaits for
tentacle 2D robots, we add a developmental process over the robots'
morphologies. Within a generation, the morphology of the robots does not
change. But from one generation to the next, the morphology develops. Much like
we become bigger, stronger, and heavier as we age, our robots are bigger,
stronger and heavier with each passing generation. Our robots start with baby
morphologies, and a few thousand generations later, end-up with adult ones. We
show that this produces better and qualitatively different gaits than an
evolutionary search with only adult robots, and that it prevents premature
convergence by fostering exploration. In addition, we validate our method on
voxel lattice 3D robots from the literature and compare it to a recent
evolutionary developmental approach. Our method is conceptually simple, and can
be effective on small or large populations of robots, and intrinsic to the
robot and its morphology, not the task or environment. Furthermore, by
recasting the evolutionary search as a learning process, these results can be
viewed in the context of developmental learning robotics.
