RT ontology development and human preference learning for assistive robotic service system

Lam Trung Ngo, Makoto Mizukawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In service robotics systems, understanding the relationship between environmental objects and user intention is the key feature to provide suitable services according to context. RT Ontology has shown to be an efficient technique to represent this relationship, yet it contains non-context information. In this paper, we propose a novel method to develop the RT Ontology automatically and a learning algorithm to connect the context-free model of RT Ontology with human preference. Resulting system is capable of providing assistive contextual services to user, as well as learning human action preference.

Original languageEnglish
Title of host publicationICCAS 2010 - International Conference on Control, Automation and Systems
Pages385-388
Number of pages4
Publication statusPublished - 2010 Dec 1
EventInternational Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of
Duration: 2010 Oct 272010 Oct 30

Publication series

NameICCAS 2010 - International Conference on Control, Automation and Systems

Conference

ConferenceInternational Conference on Control, Automation and Systems, ICCAS 2010
CountryKorea, Republic of
CityGyeonggi-do
Period10/10/2710/10/30

    Fingerprint

Keywords

  • Common sense
  • Context understanding
  • RT ontology
  • Robotic service

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

Cite this

Ngo, L. T., & Mizukawa, M. (2010). RT ontology development and human preference learning for assistive robotic service system. In ICCAS 2010 - International Conference on Control, Automation and Systems (pp. 385-388). [5669879] (ICCAS 2010 - International Conference on Control, Automation and Systems).