Evolving embodied intelligence from materials to machines

Agoston E. Eiben, David Howard, Danielle Frances Kennedy, Jean-Baptiste Mouret, Philip Valencia, Dave Winkler

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Natural lifeforms specialize to their environmental niches across many levels, from low-level features such as DNA and pro- teins, through to higher-level artefacts including eyes, limbs and overarching body plans. We propose ‘multi-level evolution’, a bottom-up automatic process that designs robots across multiple levels and niches them to tasks and environmental condi- tions. Multi-level evolution concurrently explores constituent molecular and material building blocks, as well as their possible assemblies into specialized morphological and sensorimotor configurations. Multi-level evolution provides a route to fully har- ness a recent explosion in available candidate materials and ongoing advances in rapid manufacturing processes. We outline a feasible architecture that realizes this vision, highlight the main roadblocks and how they may be overcome, and show robotic applications to which multi-level evolution 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.
Original languageEnglish
Pages (from-to)12-19
Number of pages8
JournalNature Machine Intelligence
Volume1
Publication statusPublished - 7 Jan 2019

Fingerprint Dive into the research topics of 'Evolving embodied intelligence from materials to machines'. Together they form a unique fingerprint.

  • Cite this

    Eiben, A. E., Howard, D., Kennedy, D. F., Mouret, J-B., Valencia, P., & Winkler, D. (2019). Evolving embodied intelligence from materials to machines. Nature Machine Intelligence, 1, 12-19.