Abstract
In social robotic systems, robots interact with humans to collaborate for different tasks. In this paper we consider industrial scenarios, where a shop floor can be reconfigured and specific tasks can be assigned to robots that operate as assistants to human operators. We propose to use a Knowledge Representation approach to describe the human-robot interaction. In particular, the conceptual framework based on the Generalized World Entities paradigm is adopted to capture both the physical entities of the system and events, situations, behaviours as well as the relationships among them. The paper applies the methodologies to some real case studies of the Kleeman manufacturer to automated bending machine procedures and intra-shop floor transportation with automated guided vehicles.
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References
Lu, Y., Asghar, M.R.: Semantic communications between distributed cyber-physical systems towards collaborative automation for smart manufacturing. J. Manuf. Syst. 55, 348–359 (2020)
Schramm, J., Andelfinger, U., Fischer, H., Rausch, A.: Semantically valid integration of development processes and toolchains. Systems 10(2), 40 (2022)
Larioui, J., El Byed, A.: Towards a semantic layer design for an advanced intelligent multimodal transportation system. Int. J. Adv. Trends Comput. Sci. Eng. (2020)
Li, J., Sun, L., Zhan, W., Tomizuka, M.: Interaction-aware behavior planning for autonomous vehicles validated with real traffic data. In: Dynamic Systems and Control Conference, vol. 84287. American Society of Mechanical Engineers (2020)
Sakai, T., Nagai, T.: Explainable autonomous robots: a survey and perspective. Adv. Robot. 1–20 (2022)
Mahieu, C., Ongenae, F., De Backere, F., Bonte, P., De Turck, F., Simoens, P.: Semantics-based platform for context-aware and personalized robot interaction in the internet of robotic things. J. Syst. Softw. 149, 138–157 (2019)
Manzoor, S., et al.: Ontology-based knowledge representation in robotic systems: a survey oriented toward applications. Appl. Sci. 11(10), 4324 (2021)
Pignaton de Freitas, E., et al.: Ontological concepts for information sharing in cloud robotics. J. Ambient Intell. Human. Comput. 1–12 (2020)
Schlenoff, C.I., et al.: Agile Industrial Robots (2022)
Paulius, D., Sun, Y.: A survey of knowledge representation in service robotics. Robot. Auton. Syst. 118, 13–30 (2019)
Olivares-Alarcos, A., et al.: A review and comparison of ontology-based approaches to robot autonomy. Knowl. Eng. Rev. 34 (2019)
Diab, M., Akbari, A., UdDin, M., Rosell, J.: PMK - A knowledge processing framework for autonomous robotics perception and manipulation. Sensors 19(5), 1166 (2019)
Palo, H.K.: Semantic IoT: the key to realizing IoT value. In: Pandey, R., Paprzycki, M., Srivastava, N., Bhalla, S., Wasielewska-Michniewska, K. (eds.) Semantic IoT: Theory and Applications. SCI, vol. 941, pp. 81–102. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-64619-6_4
Sampath Kumar, V., et al.: Ontologies for Industry 4.0. Knowl. Eng. Rev. 34, E17 (2019)
Azevedo, H., Belo, J.P.R., Romero, R.A. OntPercept: a perception ontology for robotic systems. In: Proceedings of the 2018 IEEE Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE), Joao Pessoa, Brazil, pp. 469–475 (2018)
Cupek, R., Fojcik, M., Gaj, P., Stój, J.: Ontology-based approaches for communication with autonomous guided vehicles for industry 4.0. In: Wojtkiewicz, K., Treur, J., Pimenidis, E., Maleszka, M. (eds.) ICCCI 2021. CCIS, vol. 1463, pp. 485–497. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-88113-9_39
Chang, D.S., Cho, G.H., Choi, Y.S.: Ontology-based knowledge model for human-robot interactive services. In: Proceedings of the 35th Annual ACM Symposium on Applied Computing, Brno, Czech Republic, pp. 2029–2038 (2020)
Dimitropoulos, K., Hatzilygeroudis, I.: Context representation and reasoning in robotics-an overview. In: Virvou, M., Tsihrintzis, G.A., Tsoukalas, L.H., Jain, L.C. (eds.) Advances in Artificial Intelligence-based Technologies. LAIS, vol. 22, pp. 79–92. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-80571-5_6
Amarilli, F., Amigoni, F., Fugini, M.G., Zarri, G.P.: A semantic-rich approach to IoT using the generalized world entities paradigm. In: Managing the Web of Things, pp. 105–147. Morgan Kaufmann (2017)
Zarri, G.P.: Using a high-level conceptual model as a support for the generalized world entities (GWEs) paradigm. In: ICIST 2020 Proceedings of the 10th International Conference on Information Systems and Technologies, Article No. 39, pp. 1–8 (2020)
Zarri, G.P.: IoT semantic modeling using the GWE (generalized world entities) paradigm. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S. (eds.) WorldCIST’18 2018. AISC, vol. 745, pp. 549–560. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-77703-0_54
Zarri, G.P.: Knowledge representation and reasoning according to an advanced n-ary model. In: 2019 Third IEEE International Conference on Robotic Computing (IRC), pp. 373–376. IEEE (2019)
Lyazid, S.: Internet of robot things in a dynamic environment: narrative-based knowledge representation and reasoning. In: Hara, T., Yamaguchi, H. (eds.) MobiQuitous 2021. LNICS, Social Informatics and Telecommunications Engineering, vol. 419, pp. 520–526. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-94822-1_33
Abdelkawy, H., Ayari, N., Chibani, A., Amirat, Y., Attal, F.: Spatio-temporal convolutional networks and n-ary ontologies for human activity-aware robotic system. IEEE Robot. Autom. Lett. 6(2), 620–627 (2020)
Acknowledgements
This work is partially supported by the H2020 “Working Age” Project https://www.workingage.eu under grant agreement No. 826232 and by the “Seamless” Regional Project in the context of the Smart Cities Programme.
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Comai, S., Finocchi, J., Fugini, M.G., Mastos, T., Papadopoulos, A. (2022). Sharing Semantic Knowledge for Autonomous Robots: Cooperation for Social Robotic Systems. In: Pardede, E., Delir Haghighi, P., Khalil, I., Kotsis, G. (eds) Information Integration and Web Intelligence. iiWAS 2022. Lecture Notes in Computer Science, vol 13635. Springer, Cham. https://doi.org/10.1007/978-3-031-21047-1_4
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