University of Hertfordshire

By the same authors

Collection of Metaphors for Human-Robot Interaction

Research output: Chapter in Book/Report/Conference proceedingConference contribution


  • Patrícia Alves-Oliveira
  • Maria Luce Lupetti
  • Michal Luria
  • Diana Löffler
  • Mafalda Gamboa
  • Lea Albaugh
  • Waki Kamino
  • Anastasia Ostrowski
  • David Puljiz
  • Pedro Reynolds-Cuéllar
  • Marcus Scheunemann
  • Michael Suguitan
  • Dan Lockton
View graph of relations
Original languageEnglish
Title of host publicationProceedings of the 2021 ACM:
Subtitle of host publicationDesigning Interactive Systems Conference
PublisherAssociation for Computing Machinery (ACM)
Number of pages14
ISBN (Print)9781450384766
Publication statusPublished - 28 Jun 2021
EventDesigning Interactive Systems Conference 2021: Nowhere and Everywhere - Virtual Event, United States
Duration: 28 Jun 20212 Jul 2021


ConferenceDesigning Interactive Systems Conference 2021
Country/TerritoryUnited States
Internet address


The word "robot" frequently conjures unrealistic expectations of utilitarian perfection: tireless, efficient, and flawless agents. However, real-world robots are far from perfect—they fail and make mistakes. Thus, roboticists should consider altering their current assumptions and cultivating new perspectives that account for a more complete range of robot roles, behaviors, and interactions. To encourage this, we explore the use of metaphors for generating novel ideas and reframing existing problems, eliciting new perspectives of human-robot interaction. Our work makes two contributions. We (1) surface current assumptions that accompany the term "robots," and (2) present a collection of alternative perspectives of interaction with robots through metaphors. By identifying assumptions, we provide a comprehensible list of aspects to reconsider regarding robots’ physicality, roles, and behaviors. Through metaphors, we propose new ways of examining how we can use, relate to, and co-exist with the robots that will share our future.


© 2021 Association for Computing Machinery. This is the accepted manuscript version of an article which has been published in final form at

Research outputs

ID: 25535339