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.