MetaMorph -- A Metamodelling Approach For Robot Morphology

TL;DR

MetaMorph is a comprehensive framework that uses a metamodeling approach to classify and compare robot morphologies, enabling better understanding of how design influences human-robot interaction.

Contribution

The paper introduces MetaMorph, a novel metamodeling framework that classifies robot morphology across all types, facilitating design optimization for various tasks.

Findings

Synthesized from 222 robots in IEEE Robots Guide

Enables assessment of visual distances between robot models

Supports exploration of optimal design traits for interaction

Abstract

Robot appearance crucially shapes Human-Robot Interaction (HRI) but is typically described via broad categories like anthropomorphic, zoomorphic, or technical. More precise approaches focus almost exclusively on anthropomorphic features, which fail to classify robots across all types, limiting the ability to draw meaningful connections between robot design and its effect on interaction. In response, we present MetaMorph, a comprehensive framework for classifying robot morphology. Using a metamodeling approach, MetaMorph was synthesized from 222 robots in the IEEE Robots Guide, offering a structured method for comparing visual features. This model allows researchers to assess the visual distances between robot models and explore optimal design traits tailored to different tasks and contexts.