Knowledge Representation for Culturally Competent Personal Robots: Requirements, Design Principles, Implementation, and Assessment

  • Barbara BrunoEmail author
  • Carmine Tommaso Recchiuto
  • Irena Papadopoulos
  • Alessandro Saffiotti
  • Christina Koulouglioti
  • Roberto Menicatti
  • Fulvio Mastrogiovanni
  • Renato Zaccaria
  • Antonio Sgorbissa


Culture, intended as the set of beliefs, values, ideas, language, norms and customs which compose a person’s life, is an essential element to know by any robot for personal assistance. Culture, intended as that person’s background, can be an invaluable source of information to drive and speed up the process of discovering and adapting to the person’s habits, preferences and needs. This article discusses the requirements posed by cultural competence on the knowledge management system of a robot. We propose a framework for cultural knowledge representation that relies on (i) a three-layer ontology for storing concepts of relevance, culture-specific information and statistics, person-specific information and preferences; (ii) an algorithm for the acquisition of person-specific knowledge, which uses culture-specific knowledge to drive the search; (iii) a Bayesian Network for speeding up the adaptation to the person by propagating the effects of acquiring one specific information onto interconnected concepts. We have conducted a preliminary evaluation of the framework involving 159 Italian and German volunteers and considering 122 among habits, attitudes and social norms.


Culture-aware robotics Companion robot Knowledge representation 



We are grateful to reviewer 3 whose insightful and constructive comments have greatly improved the quality of the article, guided us in our research, and inspired us in our service as reviewers.

Funding Information

This work has been supported by the European Commission Horizon2020 Research and Innovation Programme under Grant Agreement No. 737858 (CARESSES).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Barbara Bruno
    • 1
    Email author
  • Carmine Tommaso Recchiuto
    • 1
  • Irena Papadopoulos
    • 2
  • Alessandro Saffiotti
    • 3
  • Christina Koulouglioti
    • 2
  • Roberto Menicatti
    • 1
  • Fulvio Mastrogiovanni
    • 1
  • Renato Zaccaria
    • 1
  • Antonio Sgorbissa
    • 1
  1. 1.University of GenoaGenoaItaly
  2. 2.Middlesex University Higher Education CorporationLondonUK
  3. 3.Örebro UniversityÖrebroSweden

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