  We combine MAP-Elites and highly parallelisable simulation to explore the
design space of a class of large legged robots, which stand at around 2m tall
and whose design and construction is not well-studied. The simulation is
modified to account for factors such as motor torque and weight, and presents a
reasonable fidelity search space. A novel robot encoding allows for
bio-inspired features such as legs scaling along the length of the body. The
impact of three possible control generation schemes are assessed in the context
of body-brain co-evolution, showing that even constrained problems benefit
strongly from coupling-promoting mechanisms. A two stage process in
implemented. In the first stage, a library of possible robots is generated,
treating user requirements as constraints. In the second stage, the most
promising robot niches are analysed and a suite of human-understandable design
rules generated related to the values of their feature variables. These rules,
together with the library, are then ready to be used by a (human) robot
designer as a Design Assist tool.
