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Article published In:
Interaction Studies
Vol. 22:2 (2021) ► pp.244–279

Why robots should be technical

Correcting mental models through technical architecture concepts

| CoR-Lab Bielefeld University
| CoR-Lab Bielefeld University
| Honda Research Institute Europe
| Medical Assistance Systems Bielefeld University
| Medical Assistance Systems Bielefeld University

Research in social robotics is commonly focused on designing robots that imitate human behavior. While this might increase a user’s satisfaction and acceptance of robots at first glance, it does not automatically aid a non-expert user in naturally interacting with robots, and might hurt their ability to correctly anticipate a robot’s capabilities. We argue that a faulty mental model, that the user has of the robot, is one of the main sources of confusion. In this work, we investigate how communicating technical concepts of robotic systems to users affect their mental models, and how this can increase the quality of human-robot interaction. We conducted an online study and investigated possible ways of improving users’ mental models. Our results underline that communicating technical concepts can form an improved mental model. Consequently, we show the importance of consciously designing robots that express their capabilities and limitations.

Keywords: human-robot interaction, mental models, interaction design, robot architecture, technical concepts, robot transparency
Article outline
  • 1.Introduction
  • 2.Related work
    • 2.1Dual nature of computational artifacts: Relevance and architecture
    • 2.2Relation to human interactive learning and pragmatic frames
    • 2.3Communicating technical concepts
      • 2.3.1Instructions
      • 2.3.2Feedback
  • 3.Hypotheses
  • 4.Methods
    • 4.1Scenario
    • 4.2System and concepts
      • 4.2.1Robot
        • Robotic platform
        • System
      • 4.2.2Concepts
        • Object recognition
        • Speech recognition
        • State machine
    • 4.3Experimental design
      • 4.3.1Architecture instruction video
      • 4.3.2Robot visualization
        • Marker detection for object identification
        • Verbal communication
        • Finite state machines for robot control
      • 4.3.3Course of online study
      • 4.3.4Human-robot interaction videos
        • Object detection error
        • Speech recognition error
        • State machine error
  • 5.Results
    • 5.1Hypothesis 1: Providing architectural concepts allows users to gain more knowledge about the functionality of a robot
      • Which components does the robot have that allow it to observe or interact with its environment? (hardware)
      • What skills and abilities does the robot have? (software)
    • 5.2Hypothesis 2: Insights into the architecture of a robot increases the ability to recognize and explain errors in human-robot interaction
    • 5.3Hypothesis 3: Technical concepts differ in terms of their familiarity and observability. These factors influence the user’s ability to recognize and understand problems in human-robot interactions
    • 5.4ATI, godspeed and system-usability-scale
  • 6.Discussion
  • 7.Conclusion
  • 8.Future work
  • Notes
  • References
Published online: 28 February 2022
DOI logo
https://doi.org/10.1075/is.20023.hin
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