Iris - A knowledge Graph-based chatbot for Explaining Robotic Scenario Information to Human Operators in a Retail Setting

Master Thesis (2023)
Author(s)

K. Xu (TU Delft - Mechanical Engineering)

Contributor(s)

Carlos Hernández – Mentor (TU Delft - Robot Dynamics)

P.R. Mercuriali – Coach (TU Delft - Robot Dynamics)

Y. B. B. Eisma – Graduation committee member (TU Delft - Human-Robot Interaction)

Corrado Pezzato – Graduation committee member (TU Delft - Robot Dynamics)

Faculty
Mechanical Engineering
Copyright
© 2023 Ke Xu
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Ke Xu
Graduation Date
21-03-2023
Awarding Institution
Delft University of Technology
Programme
['Mechanical Engineering | Vehicle Engineering | Cognitive Robotics']
Faculty
Mechanical Engineering
Reuse Rights

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Abstract

The problem of assisting users in comprehending the robotic scenario information in a retail setting has been studied. To design the system, an integrated ontology composed of several IEEE standard ontologies and a labelled property graph (LPG)-based ontology modified from the Web Ontology Language (OWL)-based ontology was proposed to symbolize information in the robotic environment. Then, a knowledge graph (KG)-based chatbot was developed to provide natural language interaction with users. A case study in a retail setting was designed, and the results were analyzed. The effectiveness of our designed system has been experimentally validated in both static and dynamic scenarios, with at least 1.5 times improvements.

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