Giraff Meets KOaLa to Better Reason on Sensor Networks

  • Amedeo Cesta
  • Luca Coraci
  • Gabriella Cortellessa
  • Riccardo De Benedictis
  • Andrea Orlandini
  • Alessandra Sorrentino
  • Alessandro UmbricoEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 539)


Recent technological advancements in Internet of Things and Cyber-Physical systems are fostering the diffusion of smart environments relying on sensor networks. Indeed, large and heterogeneous amount of data can be provided by sensors deployed in user environments providing valuable knowledge to address different user needs and enabling more effective and reliable solutions as well as ensuring personalization and dynamic adaptation. This paper presents a recent research initiative whose aim is to realize autonomous and socially interacting robots by integrating sensor data representation and knowledge reasoning with decision making functionalities within a cognitive control architecture, called Knowledge-based cOntinuous Loop (KOaLa).


Intelligent environments Knowledge representation Ontology Sensor networks Artificial intelligence 


  1. 1.
    Alirezaie, M., Renoux, J., Kockemann, U., Loutfi, A.: An ontology-based context-aware system for smart homes: E-care@home. Sensors 17(7) (2017)CrossRefGoogle Scholar
  2. 2.
    Alirezaie, M., Loutfi, A.: Reasoning for improved sensor data interpretation in a smart home. CoRR abs/1412.7961 (2014).
  3. 3.
    Awaad, I., Kraetzschmar, G.K., Hertzberg, J.: The role of functional affordances in socializing robots. Int. J. Soc. Robot. 7(4), 421–438 (2015). Scholar
  4. 4.
    Bechhofer, S.: OWL: Web Ontology Language, pp. 2008–2009. Springer, Boston (2009). Scholar
  5. 5.
    Behnke, G., Ponomaryov, D., Schiller, M., Bercher, P., Nothdurft, F., Glimm, B., Biundo, S.: Coherence across components in cognitive systems–one ontology to rule them all. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2015). AAAI Press (2015)Google Scholar
  6. 6.
    Cialdea Mayer, M., Orlandini, A., Umbrico, A.: Planning and execution with flexible timelines: a formal account. Acta Informatica 53(6–8), 649–680 (2016)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Compton, M., et al.: The SSN ontology of the W3C semantic sensor network incubator group. Web Semant Sci. Serv. Agents World Wide Web 17(Supplement C), 25–32 (2012). Scholar
  8. 8.
    Coradeschi, S., Cesta, A., Cortellessa, G., Coraci, L., Gonzalez, J., Karlsson, L., Furfari, F., Loutfi, A., Orlandini, A., Palumbo, F., Pecora, F., von Rump, S., Štimec, A., Ullberg, J., Ötslund, B.: Giraffplus: combining social interaction and long term monitoring for promoting independent living. In: 2013 6th International Conference on Human System Interactions (HSI), pp. 578–585 (2013)Google Scholar
  9. 9.
    Hartanto, R., Hertzberg, J.: Fusing DL Reasoning with HTN Planning. In: Dengel, A., Berns, K., Breuel, T., Bomarius, F., Roth-Berghofer, T. (eds.) KI 2008: Advances in Artificial Intelligence, Lecture Notes in Computer Science, vol. 5243, pp. 62–69. Springer, Heidelberg (2008).
  10. 10.
    Keckemann, U., Pecora, F., Karlsson, L.: Inferring context and goals for online human-aware planning. In: 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 550–557 (2015)Google Scholar
  11. 11.
    Lemaignan, S., Ros, R., Mosenlechner, L., Alami, R., Beetz, M.: ORO, a knowledge management platform for cognitive architectures in robotics. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3548–3553 (2010)Google Scholar
  12. 12.
    Pecora, F., Cirillo, M., Dell’Osa, F., Ullberg, J., Saffiotti, A.: A constraint-based approach for proactive, context-aware human support. JAISE 4(4), 347–367 (2012)Google Scholar
  13. 13.
    Suh, I.H., Lim, G.H., Hwang, W., Suh, H., Choi, J.H., Park, Y.T.: Ontology-based multi-layered robot knowledge framework (OMRKF) for robot intelligence. In: 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007, pp. 429–436 (2007)Google Scholar
  14. 14.
    Tenorth, M., Beetz, M.: Representations for robot knowledge in the KnowRob framework. Artif. Intell. (2015). Scholar
  15. 15.
    Umbrico, A., Cesta, A., Cialdea Mayer, M., Orlandini, A.: PLATINUm: a new framework for planning and acting, pp. 508–522. Springer International Publishing, Cham (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Amedeo Cesta
    • 1
  • Luca Coraci
    • 1
  • Gabriella Cortellessa
    • 1
  • Riccardo De Benedictis
    • 1
  • Andrea Orlandini
    • 1
  • Alessandra Sorrentino
    • 1
  • Alessandro Umbrico
    • 1
    Email author
  1. 1.National Research Council of Italy, Institute of Cognitive Sciences and Technologies (ISTC-CNR)RomeItaly

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