Engineering Background Knowledge for Social Robots

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Social robots are embodied agents that perform knowledge-intensive tasks involving several kinds of information from different heterogeneous sources. This book, Engineering Background Knowledge for Social Robots, introduces a component-based architecture for supporting the knowledge-intensive tasks performed by social robots. The design was based on the requirements of a real socially-assistive robotic application, and all the components contribute to and benefit from the knowledge base which is its cornerstone. The knowledge base is structured by a set of interconnected and modularized ontologies which model the information, and is initially populated with linguistic, ontological and factual knowledge retrieved from Linked Open Data. Access to the knowledge base is guaranteed by Lizard, a tool providing software components, with an API for accessing facts stored in the knowledge base in a programmatic and object-oriented way. The author introduces two methods for engineering the knowledge needed by robots, a novel method for automatically integrating knowledge from heterogeneous sources with a frame-driven approach, and a novel empirical method for assessing foundational distinctions over Linked Open Data entities from a common-sense perspective. These effectively enable the evolution of the robot s knowledge by automatically integrating information derived from heterogeneous sources and the generation of common-sense knowledge using Linked Open Data as an empirical basis. The feasibility and benefits of the architecture have been assessed through a prototype deployed in a real socially-assistive scenario, and the book presents two applications and the results of a qualitative and quantitative evaluation.

Author(s): Luigi Asprino
Series: Studies on the Semantic Web
Publisher: IOS Press
Year: 2020

Language: English
Pages: 238
City: Berlin

Title Page
Abstract
Contents
Introduction
Goals of the Thesis
Contributions of the Thesis
An Ontology Network for Social Robots in Assistive Context
Research Methodology
Thesis Outline
Background
Social Robots
The Semantic Web
Ontologies
Pattern-based Ontology Design
Ontology Matching
Linguistic Linked Open Data Resources
Common Sense Knowledge
An Ontology Network for Social Robots in Assistive Context
Design Methodology
Knowledge Areas
Ontology Modules
Discussion
Providing Linked Open Data as Background Knowledge for Social Robots
Framester: a Linguistic Data Hub
Assessing Foundational Distinctions in Linked Open Data
Discussion
Accessing Background Knowledge using Lizard
Requirements
Architecture
Ontology Bundle
Discussion
A Frame-based Approach for Integrating Ontologies
Types of Semantic Heterogeneity
Proposed Approach
Discussion
A Knowledge Base Centered Software Architecture for Social Robots
Requirements of Software Architectures for Social Robots
Robot Software Architecture Overview
Components
Architecture Prototype for a Real Social Assistive Scenario
Discussion
Conclusion and Future Work
Research Questions Revisited
Future Work
Code Generated by Lizard
Interface
Jena Class
Bean Class
REST API Description
Bibliography