Abstract
Mobile robots are becoming more and more ubiquitous in our everyday living environments. Therefore, it is very important that people can easily interpret what the robot’s intentions are. This is especially important when a robot is driving down a crowded corridor. It is essential for people in its vicinity to understand which way the robot wants to go next. To explore what signals are the best for conveying its intention to turn, we implemented three lighting schemes and tested them out in an online experiment. We found that signals resembling automotive signaling work the best also for logistic mobile robots. We further find that people’s opinion of these signaling methods will be influenced by their demographic background (gender, age).
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Notes
- 1.
See a video of the implemented conditions here https://youtu.be/J6jtDH6ZSuw.
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This work was supported by the project Health-CAT, funded by the European Regional Development Fund.
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Palinko, O., Ramirez, E.R., Krüger, N., Bodenhagen, L. (2022). Intention Understanding for Human-Aware Mobile Robots: Comparing Cues and the Effect of Demographics. In: Bouatouch, K., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2020. Communications in Computer and Information Science, vol 1474. Springer, Cham. https://doi.org/10.1007/978-3-030-94893-1_4
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DOI: https://doi.org/10.1007/978-3-030-94893-1_4
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