Abstract
Personalization and localization are essential when developing social robots for different sectors, including education, industry, healthcare or restaurants. This requires adjusting the robot's behavior to an individual's needs, preferences, or personality when referring to personalization or the social convention or country's culture when referring to localization. Current literature presents different models that enable personalization and localization, each with its advantages and drawbacks. This work aims to help researchers in social robotics by reviewing and analyzing different papers in this domain. We focus our review on exploring various technical methods used to make decisions and adapt social robots’ non-verbal and verbal skills, including the state-of-the-art techniques in the sector of artificial intelligence.
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Acknowledgment
The project was supported by the Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. 2020–0-00842, Development of Cloud Robot Intelligence for Continual Adaptation to User Reactions in Real Service Environments).
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Hellou, M., Gasteiger, N., Ahn, H.S. (2021). Personalization and Localization to Improve Social Robots’ Behaviors: A Literature Review. In: Li, H., et al. Social Robotics. ICSR 2021. Lecture Notes in Computer Science(), vol 13086. Springer, Cham. https://doi.org/10.1007/978-3-030-90525-5_68
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DOI: https://doi.org/10.1007/978-3-030-90525-5_68
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