Desiging robot services with ontology and learning

Authors:
Chiung-Hon Leon Lee;Alan Liu
Affiliations:
Department of Computer Science and Information Engineering, Nanhua University, Chia-Yi, Taiwan;Department of Electrical Engineering and Center for Telecommunication Research, National Chung Cheng University, Chia-Yi, Taiwan
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

Citing 5
Cited 0

Case-based reasoning: foundational issues, methodological variations, and system approaches

AI Communications
User Intention Satisfaction for Agent-Based Semantic Web Services Systems

APSEC '05 Proceedings of the 12th Asia-Pacific Software Engineering Conference
Representation in case-based reasoning

The Knowledge Engineering Review
From Abstract Task Knowledge to Executable Robot Programs

Journal of Intelligent and Robotic Systems
A Flexible Architecture for Navigation Control of a Mobile Robot

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Quantified Score

Hi-index	0.00

Visualization

Abstract

Considering user preferences in defining robot services is important. How to interact with service robots varies from user to user, and providing a user friendly way for the users to interact with robots becomes necessary since the users are usually non-technical people when dealing with service robots. This article focuses on defining robot services that can suit user's preferences. Service robots are typically designed to provide one set of services not targeted to a particular user. However, ways of controlling robots may differ depending on users. Learning from past experiences enables a robot to adapt to the user's specific needs and interacting style. In this research, we use ontology as the design tool for defining robot services and uses case-based reasoning as a means of learning in storing previous interaction experiences as cases. These cases are reused the next time when similar requests are made.