Abstract
This paper investigates how user pre-experience impacts the quality of Human-Robot Interaction (HRI) when using a virtual reality (VR) interface to control a robot. The benefit lies in the fact that creating interfaces for these complex systems is a challenging process, and our aim is to shed light on one of the contributing factors. We aim to complement existing works by conducting a user study exploring the link between multiple psychological factors and users’ pre-experience with robot systems, video games and gamepads while interacting with a real robot through a VR interface. Results showed that experienced users reported less cognitive load, but also less trustworthiness of and satisfaction with the system and that these factors are correlated with system usability and satisfaction. We assume that this is based in pre-experienced users, having higher expectations and a more critical perception of new systems. These findings could guide the development of future interfaces tailored to specific user groups.
Keywords
- Human-Robot Interaction
- Virtual Reality
- Trust
- Trustworthiness
- Cognitive Load
- Satisfaction
Supported by the Austrian Research Promotion Agency (FFG) - KIRAS Program - Project EASIER (FO999886357).
This is a preview of subscription content, access via your institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ahmad, M.I., Bernotat, J., Lohan, K., Eyssel, F.: Trust and cognitive load during human-robot interaction (2019). arXiv:1909.05160 [cs]
Aubert, B.A.: The impact of interface quality on trust in web retailers. Cahier du GReSI no 1(05) (2001)
Brooke, J., et al.: SUS-A quick and dirty usability scale. Usabil. Eval. Ind. 189(194), 4–7 (1996)
Chang, E., Kim, H.T., Yoo, B.: Virtual reality sickness: a review of causes and measurements. Int. J. Hum.-Comput. Interact. 36(17), 1658–1682 (2020)
Dianatfar, M., Latokartano, J., Lanz, M.: Review on existing VR/AR solutions in human-robot collaboration. Proc. CIRP 97, 407–411 (2021)
Fox, D., Burgard, W., Thrun, S.: The dynamic window approach to collision avoidance. IEEE Robot. Autom. Mag. 4(1), 23–33 (1997). https://doi.org/10.1109/100.580977
Frering, L., et al.: Enabling and assessing trust when cooperating with robots in disaster response (EASIER) (2022). http://arxiv.org/abs/2207.03763
Gasteiger, N., Hellou, M., Ahn, H.S.: Factors for personalization and localization to optimize human–robot interaction: a literature review. Int. J. Soc. Robot. 1–13 (2021)
Hart, S.G., Staveland, L.E.: Development of NASA-TLX (task load index): results of empirical and theoretical research. In: Advances in Psychology, vol. 52, pp. 139–183. Elsevier (1988). https://doi.org/10.1016/S0166-4115(08)62386-9
Khavas, Z.R.: A review on trust in human-robot interaction. arXiv preprint arXiv:2105.10045 (2021)
Khundam, C.: A study on usability and motion sickness of locomotion techniques for virtual reality. ECTI Trans. Comput. Inf. Technol. (ECTI-CIT) 15(3), 347–361 (2021)
Kim, Y.D., Kang, J.H., Sun, D.H., Moon, J.I., Ryuh, Y.S., An, J.: Design and implementation of user friendly remote controllers for rescue robots in fire sites. In: Proceedings of SICE Annual Conference 2010, pp. 875–880. IEEE (2010)
Körber, M.: Theoretical considerations and development of a questionnaire to measure trust in automation. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds.) IEA 2018. AISC, vol. 823, pp. 13–30. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-96074-6_2
Lewis, J.R.: Psychometric evaluation of the PSSUQ using data from five years of usability studies. Int. J. Hum.-Comput. Interact. 14(3–4), 463–488 (2002)
Longo, L.: Experienced mental workload, perception of usability, their interaction and impact on task performance. PLoS One 13(8), e0199661 (2018). https://doi.org/10.1371/journal.pone.0199661
Michalos, A.C.: Satisfaction and happiness. Soc. Indic. Res. 8, 385–422 (1980)
Nenna, F., Gamberini, L.: The influence of gaming experience, gender and other individual factors on robot teleoperations in VR. In: 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 945–949. IEEE, Sapporo (2022). https://doi.org/10.1109/HRI53351.2022.9889669
Pütz, S., Simón, J.S., Hertzberg, J.: Move base flex: a highly flexible navigation framework for mobile robots. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018)
Wang, Z., Reed, I., Fey, A.M.: Toward intuitive teleoperation in surgery: human-centric evaluation of teleoperation algorithms for robotic needle steering. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 5799–5806. IEEE, Brisbane (2018). https://doi.org/10.1109/ICRA.2018.8460729
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Frering, L. et al. (2023). Impact of Robot Related User Pre-experience on Cognitive Load, Trust, Trustworthiness and Satisfaction with VR Interfaces. In: Petrič, T., Ude, A., Žlajpah, L. (eds) Advances in Service and Industrial Robotics. RAAD 2023. Mechanisms and Machine Science, vol 135. Springer, Cham. https://doi.org/10.1007/978-3-031-32606-6_15
Download citation
DOI: https://doi.org/10.1007/978-3-031-32606-6_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-32605-9
Online ISBN: 978-3-031-32606-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)