Masters Thesis Proposals
Drone Failures in Human Drone Interactions
Unmanned Aerial Vehicles (UAVs) such as drones are becoming increasingly common and have applications in contexts such as exploration and search and rescue, where humans might not be able to easily access such spaces. In this sense, drones are not only a technical tool, but can be perceived as a social agent capable of communicating information to a user about the environment. Yet, studies which focus on the social aspect of interactions between humans and drones are scarce. Furthermore, there are opportunities for errors to occur in such interactions (e.g., imperfect sensors, battery drain, other malfunctions) which can affect the quality and success of the human-drone communication. Consequently, this research project will explore how technological breakdowns of drone robots are perceived by human users.
Useful skills
- Programming experience (python, C++)
- Interest in Human Robot Interaction
- Knowledge of basic experimental design
- Descriptive and Inferential Statistics
Start: Anytime
Contact: Rebecca Stower
Keywords: Human-Robot Interaction, robot failures, user studies
References
D. Tezza and M. Andujar, "The State-of-the-Art of Human–Drone Interaction: A Survey," in IEEE Access, vol. 7, pp. 167438-167454, 2019, doi: 10.1109/ACCESS.2019.2953900.
Viviane Herdel, Lee J. Yamin, and Jessica R. Cauchard. 2022. Above and Beyond: A Scoping Review of Domains and Applications for Human-Drone Interaction. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI '22). Association for Computing Machinery, New York, NY, USA, Article 463, 1–22. https://doi.org/10.1145/3491102.3501881
How many ways can things go wrong? Exploring different kinds of robot errors in human robot interaction
How a robot behaves during an interaction in terms of its social behaviours (e.g., gaze, proxemics, non-verbal behaviours) has been demonstrated to effect human’s perceptions of the robot as a social agent. In parallel, recent research has begun to explore how robot failures also impact the interaction in terms of the robot’s perceived competence. A taxonomy of robot errors has also been proposed. To this end, this research project aims to compare how different kinds of robot errors affect participants perceived competence, social desirability, and perceived agency of the robot.
Useful skills
- Programming experience (python, C++)
- Interest in Human Robot Interaction
- Knowledge of basic experimental design
- Descriptive and Inferential Statistics
Start: Anytime
Contact: Rebecca Stower
Keywords: Human-Robot Interaction, robot failures, user studies
References
Tatarian, K., Stower, R., Rudaz, D. et al. How does Modality Matter? Investigating the Synthesis and Effects of Multi-modal Robot Behavior on Social Intelligence. Int J of Soc Robotics 14, 893–911 (2022). https://doi.org/10.1007/s12369-021-00839-w
Suzanne Tolmeijer, Astrid Weiss, Marc Hanheide, Felix Lindner, Thomas M. Powers, Clare Dixon, and Myrthe L. Tielman. 2020. Taxonomy of Trust-Relevant Failures and Mitigation Strategies. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI '20). Association for Computing Machinery, New York, NY, USA, 3–12. https://doi.org/10.1145/3319502.3374793
Honig, S., & Oron-Gilad, T. (2018). Understanding and resolving failures in human-robot interaction: Literature review and model development. Frontiers in psychology, 9, 861.
