Evolutionary developmental soft robotics: Towards adaptive and intelligent soft machines following nature’s approach to design

Abstract

Despite many recent successes in robotics and artificial intelligence, robots are still far from matching the performances of biological creatures outside controlled environments, mainly due to their lack of adaptivity. By taking inspiration from nature, bio-robotics and soft robotics have pointed out new directions towards this goal, showing a lot of potential. However, in many ways, this potential is still largely unexpressed. Three main limiting factors can be identified: (1) the common adoption of non-scalable design processes constrained by human capabilities, (2) an excessive focus on proximal solutions observed in nature instead of on the natural processes that gave rise to them, (3) the lack of general insights regarding intelligence, adaptive behavior, and the conditions under which they emerge in nature. By adopting algorithms inspired by the natural evolution and development, evolutionary developmental soft robotics represents in a way the ultimate form of bio-inspiration. This approach allows the automated design of complete soft robots, whose morphology, control, and sensory system are co-optimized for different tasks and environments, and can adapt in response to environmental stimuli during their lifetime. This can be useful for several purposes, from the evolutionary design of soft robots for practical applications, to the study of general properties of soft bodied creatures, which could help realizing the full potential of this field.