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ORKA: An Ontology for Robotic Knowledge Acquisition

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Knowledge Engineering and Knowledge Management (EKAW 2024)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 15370))

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Abstract

Most autonomous agents operating in the real world use perception capabilities and reasoning mechanisms to acquire new knowledge of the environment, where perception capabilities include both the physical sensor devices and the software-based perception pipelines involved in the process. For autonomous agents to be able to adjust and reason over their own perception, knowledge of the sensors and the corresponding perception algorithms is required. We present the Ontology for Robotic Knowledge Acquisition (ORKA), that models the perception pipeline of a robotic agent by representing the sensory, algorithmic and measurement aspects of the perception process, thereby unifying the agent’s sensing with the characteristics of the environment and facilitating the grounding process. The ontology is based on the alignment between SSN and OBOE, linked to external databases as additional knowledge sources for robotic agents, populated with instances from two different robotic use-cases, and evaluated using competency questions and comparisons to related ontologies. A proof of concept use-case is presented to highlight the potential of the ontology.

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Notes

  1. 1.

    We consider a “perception algorithm” any algorithmic process that results in new observations about characteristics of objects.

  2. 2.

    https://github.com/Dorteel/orka.

  3. 3.

    http://caressesrobot.org/ontology/.

  4. 4.

    https://pytorch.org/hub/ultralytics_yolov5/.

  5. 5.

    https://github.com/Dorteel/orka.

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Authors and Affiliations

  1. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Mark Adamik, Romana Pernisch, Ilaria Tiddi & Stefan Schlobach

  2. Discovery Lab, Elsevier, Amsterdam, The Netherlands

    Romana Pernisch

Authors
  1. Mark Adamik
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  2. Romana Pernisch
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  3. Ilaria Tiddi
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  4. Stefan Schlobach
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Corresponding author

Correspondence to Mark Adamik .

Editor information

Editors and Affiliations

  1. Télécom Paris, Institut Polytechnique de Paris, Palaiseau, France

    Mehwish Alam

  2. Università degli Studi di Verona, Verona, Italy

    Marco Rospocher

  3. KNAW Humanities Cluster, Amsterdam, The Netherlands

    Marieke van Erp

  4. Centrum Wiskunde and Informatica, Amsterdam, The Netherlands

    Laura Hollink

  5. FIZ Karlsruhe, Eggenstein-Leopoldshafen, Germany

    Genet Asefa Gesese

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Adamik, M., Pernisch, R., Tiddi, I., Schlobach, S. (2025). ORKA: An Ontology for Robotic Knowledge Acquisition. In: Alam, M., Rospocher, M., van Erp, M., Hollink, L., Gesese, G.A. (eds) Knowledge Engineering and Knowledge Management. EKAW 2024. Lecture Notes in Computer Science(), vol 15370. Springer, Cham. https://doi.org/10.1007/978-3-031-77792-9_19

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