Evolving embodied intelligence from materials to machines
release_72o5hnafe5agrhcyglgyui3hnu
by
David Howard and Agoston E. Eiben and Danielle Frances Kennedy and
Jean-Baptiste Mouret and Philip Valencia and Dave Winkler
2019
Abstract
Natural lifeforms specialise to their environmental niches across many
levels; from low-level features such as DNA and proteins, through to
higher-level artefacts including eyes, limbs, and overarching body plans. We
propose Multi-Level Evolution (MLE), a bottom-up automatic process that designs
robots across multiple levels and niches them to tasks and environmental
conditions. MLE concurrently explores constituent molecular and material
'building blocks', as well as their possible assemblies into specialised
morphological and sensorimotor configurations. MLE provides a route to fully
harness a recent explosion in available candidate materials and ongoing
advances in rapid manufacturing processes. We outline a feasible MLE
architecture that realises this vision, highlight the main roadblocks and how
they may be overcome, and show robotic applications to which MLE is
particularly suited. By forming a research agenda to stimulate discussion
between researchers in related fields, we hope to inspire the pursuit of
multi-level robotic design all the way from material to machine.
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