Affiliations: Institute for Software Technology, Graz University of Technology, Graz, Austria. E-mails: {sgspandl, ipill, mreip, steinbauer}@ist.tugraz.at
Note: [] The authors are listed in alphabetical order.
Note: [] Corresponding author: Gerald Steinbauer, Institute for Software Technology, Graz University of Technology, Inffeldgasse 16b/II, 8010 Graz, Austria. E-mail: steinbauer@ist.tugraz.at
Abstract: Non-deterministic reality is a severe challenge for autonomous robots. Malfunctioning actions, inaccurate sensor perception and exogenous events easily lead to inconsistencies between an actual situation and the internal knowledge-base encoding a robot's belief. For a viable reasoning in dynamic environments, a robot is thus required to efficiently cope with such inconsistencies and maintain a consistent knowledge-base as fundament for its decision-making. In this paper, we present a belief management system based on the well-known agent programming language IndiGolog and history-based diagnosis. Extending the language's default mechanisms, we add a belief management system that is capable of handling several fault types that lead to belief inconsistencies. First experiments in the domain of service robots show the effectiveness of our approach.
