  Evolutionary algorithms offer great promise for the automatic design of robot
bodies, tailoring them to specific environments or tasks. Most research is done
on simplified models or virtual robots in physics simulators, which do not
capture the natural noise and richness of the real world. Very few of these
virtual robots are built as physical robots, and the few that are will rarely
be further improved in the actual environment they operate in, limiting the
effectiveness of the automatic design process. We utilize our shape-shifting
quadruped robot, which allows us to optimize the design in its real-world
environment. The robot is able to change the length of its legs during
operation, and is robust enough for complex experiments and tasks. We have
co-evolved control and morphology in several different scenarios, and have seen
that the algorithm is able to exploit the dynamic morphology solely through
real-world experiments.
