DKA-robo: Dynamically updating time-invalid knowledge bases using robots

Abstract

In this paper we present the DKA-robo framework, where a mobile robot is used to update the statements of a knowledge base that have lost validity in time. Managing the dynamic information of knowledge bases constitutes a key issue in many real-world scenarios, because constantly reevaluating data requires efforts in terms of knowledge acquisition and representation. Our solution to such a problem is to use RDF and SPARQL to represent and manage the time validity of information, combined with a robot acting as a mobile sensor which updates the outdated statements in the knowledge base, therefore always guaranteeing time-valid results against user queries. This demo shows the implementation of our approach in the working environment of our research lab, where a robot is used to sense temperature, humidity, wifi-signal and number of people on demand, updating the lab knowledge base with time-valid information.