Evolutionary Brain-Body Co-Optimization Consistently Fails to Select for Morphological Potential

Brain-body co-optimization remains a challenging problem. To understand and overcome its challenges, we exhaustively map a morphology-fitness landscape: we train controllers for each morphology in a design space of 1,305,840 voxel-based soft robots. On the other hand, co-optimizing morphology and control creates useful goal-switching, yielding morphology-controller pairs whose performance cannot be reached by optimizing the controller alone for a fixed morphology.