Desiging Robot Services with Ontology and Learning

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.