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Using Design Metaphors to Understand User Expectations of Socially Interactive Robot Embodiments

Nathaniel Dennler, Changxiao Ruan, Jessica Hadiwijoyo, Brenna Chen, Stefanos Nikolaidis, Maja Mataric

TL;DR

This paper investigates how the physical design of socially interactive robots shapes user expectations of social and functional capabilities. It introduces a large, open dataset of 165 robot embodiments and three crowd-sourced studies (design metaphors, social perception, and functional perception) to map how embodiment cues map to expected behavior. Key findings show strong links between identity closeness and positive social judgments, while likeability does not reliably track functional expectations; anthropomorphic designs drive higher functional expectations, and metaphor abstraction modulates these expectations. The work offers practical guidance for robot designers and study designers, plus visualization and analytic tools to situate new designs within the established design space, aiming to improve human-robot interaction and align user expectations with actual capabilities.

Abstract

The physical design of a robot suggests expectations of that robot's functionality for human users and collaborators. When those expectations align with the true capabilities of the robot, interaction with the robot is enhanced. However, misalignment of those expectations can result in an unsatisfying interaction. This paper uses Mechanical Turk to evaluate user expectation through the use of design metaphors as applied to a wide range of robot embodiments. The first study (N=382) associates crowd-sourced design metaphors to different robot embodiments. The second study (N=803) assesses initial social expectations of robot embodiments. The final study (N=805) addresses the degree of abstraction of the design metaphors and the functional expectations projected on robot embodiments. Together, these results can guide robot designers toward aligning user expectations with true robot capabilities, facilitating positive human-robot interaction.

Using Design Metaphors to Understand User Expectations of Socially Interactive Robot Embodiments

TL;DR

This paper investigates how the physical design of socially interactive robots shapes user expectations of social and functional capabilities. It introduces a large, open dataset of 165 robot embodiments and three crowd-sourced studies (design metaphors, social perception, and functional perception) to map how embodiment cues map to expected behavior. Key findings show strong links between identity closeness and positive social judgments, while likeability does not reliably track functional expectations; anthropomorphic designs drive higher functional expectations, and metaphor abstraction modulates these expectations. The work offers practical guidance for robot designers and study designers, plus visualization and analytic tools to situate new designs within the established design space, aiming to improve human-robot interaction and align user expectations with actual capabilities.

Abstract

The physical design of a robot suggests expectations of that robot's functionality for human users and collaborators. When those expectations align with the true capabilities of the robot, interaction with the robot is enhanced. However, misalignment of those expectations can result in an unsatisfying interaction. This paper uses Mechanical Turk to evaluate user expectation through the use of design metaphors as applied to a wide range of robot embodiments. The first study (N=382) associates crowd-sourced design metaphors to different robot embodiments. The second study (N=803) assesses initial social expectations of robot embodiments. The final study (N=805) addresses the degree of abstraction of the design metaphors and the functional expectations projected on robot embodiments. Together, these results can guide robot designers toward aligning user expectations with true robot capabilities, facilitating positive human-robot interaction.
Paper Structure (56 sections, 2 equations, 16 figures, 2 tables)

This paper contains 56 sections, 2 equations, 16 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Background and Related Work
  3. Research Through Design
  4. Understanding Design Through Metaphors
  5. The Social Perception of Robot Embodiment:
  6. Social Perception of Robot Faces
  7. Collecting Crowd-Sourced Data on User Perceptions
  8. Data Quality
  9. Data Collection Methodology
  10. Study 1: Crowd-Sourcing Design Metaphors
  11. Study Design
  12. Qualitative Measures
  13. Overview of Collected Data
  14. Study 2: Social Perception
  15. Study Design
  16. ...and 41 more sections

Figures (16)

  • Figure 1: Examples of robots' physical designs measured by abstraction level along three different design metaphors.
  • Figure 2: Example stimuli from the database.
  • Figure 3: A t-SNE visualization of the design space of robot embodiments. Each point represents one robot in the dataset. Brown represents high values and teal represents lower values of the measured ratings.
  • Figure 4: Correlations between attributes collected through surveys. All shown correlations are significant with $p < 0.001$. Pearson's r value is shown in each square. The first six items are from the survey of social perceptions, and the next five are from the survey of functional perceptions.
  • Figure 5: Histogram of metaphor counts for metaphors that were associated with more than one robot in our dataset. An additional 129 singleton design metaphors are not shown. The specific sources of the referential metaphors (e.g., movies, shows) are removed for visualization, but were provided to participants during data collection.
  • ...and 11 more figures