Evolving embodied intelligence from materials to machines

TL;DR

This paper introduces Multi-Level Evolution (MLE), a bottom-up approach to automatically design robots by exploring materials, structures, and functions simultaneously, inspired by biological evolution across multiple levels.

Contribution

It proposes a novel MLE framework that integrates material selection, morphological design, and sensorimotor configuration for autonomous robot development.

Findings

MLE can explore a vast design space across multiple levels.

It leverages advances in materials and manufacturing for robot evolution.

The framework is suited for diverse robotic applications.

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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