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

Master thesis (2023)

Authors

K. Xu Mechanical Engineering

Contributors

Carlos Hernández Robot Dynamics - Mechanical, Maritime and Materials Engineering (mentor)
P.R. Mercuriali Robot Dynamics - Mechanical, Maritime and Materials Engineering (coach)
Y.B. Eisma Human-Robot Interaction - Mechanical, Maritime and Materials Engineering (graduation committee member)
C. Pezzato Robot Dynamics - Mechanical, Maritime and Materials Engineering (graduation committee member)
Faculty
Mechanical Engineering, Mechanical Engineering
Copyright: © 2023 Ke Xu
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Published Date

21-03-2023

Language

English

Reuse Rights

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Faculty

Mechanical Engineering

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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Ke_Xu_Master_Thesis.pdf
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File under embargo until 31-08-2024