Ontology-based Understanding of Everyday Activity Instructions

Contributors:
  1. Maria M. Hedblom
  2. Mihai Pomarlan
  3. Vanja Sophie Cangalovic
  4. Johannes Pfau
  5. John Bateman
  6. Rainer Malaka

Date created: | Last Updated:

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Description: Going from natural language instructions to fully specified executable plans for household robots, various reasoning steps are required. We propose and implement a processing pipeline to tackle these steps and use the ontological Socio-physical Model of Activities (SOMA) as a common interface between its components. One major advantage of employing an overarching ontological framework is that we can store its asserted facts alongside the semantics of instructions, contextual knowledge, and annotated activity models in one central knowledge base. This allows for a unified and efficient knowledge retrieval across all pipeline components, providing flexibility and reasoning capabilities as we combine symbolic knowledge with annotated sub-symbolic models. Using our pipeline, a robot faced with a natural language task description is able to simulate the task and thus, demonstrate its understanding.

License: CC-By Attribution 4.0 International

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Components

  • Deep Language Understanding (DLU)

    Implementation of DLU processing pipeline as used in "Ontology-based Understanding of Everyday Activity Instructions".

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  • Streaming Construction Grammar (SCG)

    Cangalovic
    SCG as used in "Ontology-based Understanding of Everyday Activity Instructions".

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  • Physics Simulator – Kitchen Scene

    The Unity physics simulator used in DLU as used in "Ontology-based Understanding of Everyday Activity Instructions".

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  • Socio-physical Model of Activities (SOMA)

    Beßler, Porzel, Pomarlan & 5 more
    SOMA as used in "Ontology-based Understanding of Everyday Activity Instructions".

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  • Publication materials

    Höffner, Porzel, Hedblom & 5 more
    Paper materials (LaTeX files, figures, ...) for "Ontology-based Understanding of Everyday Activity Instructions"

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