Improvement in service robot´s interaction through case based reasoning

In order to enable tight interaction and close collaboration between human and service robots it is necessary that robots imitate the cognitive mechanisms of the brain and their role in competent activity control. That goal can only be achieved if robots are capable of observing their environment, reasoning about it, and autonomously deciding the most appropriate action in a given situation. We present a possible application in this broad area: “Sacarino” is a service robot desingned to work as bellboy in a hotel environment as part of the ROSETEL project. In order to tackle the challenge of learning by interaction we define: (i) the scenarios in which our agent have to work, (ii) its prior knowledge in an episodic memory module to be used in a prime dialog interaction, and (iii) the proper architecture that will support intelligent behaviour suitable for the control of our robot. We will use frameworks like JCOLOBRI (Cases and Ontology Libraries Integration for Building Reasoning Infrastructures) to define the agent´s memory structure, taking a deeper look into the episodic memory of the system.