Being able to predict events and occurrences which may arise from a current situation is a desirable capability#R##N##R##N#of an intelligent agent. In this paper, we show that a high-level scene interpretation system, implemented as#R##N##R##N#part of a comprehensive robotic system developed in the XXX project, can also be used for prediction. This#R##N##R##N#way, the robot can foresee possible developments of the environment and the effect they may have on its activities. As a guiding example, we consider a robot acting as a waiter in a restaurant and the task of predicting#R##N##R##N#possible occurrences and courses of action, e.g. when serving a coffee to a guest. Our approach requires that#R##N##R##N#the robot possesses conceptual knowledge about occurrences in the restaurant and its own activities, represented in the standardized ontology language OWL and augmented by constraints using SWRL. Conceptual#R##N##R##N#knowledge may be acquired by conceptualizing experiences collected in the robotâs memory. Predictions#R##N##R##N#are generated by a model-construction process which seeks to explain evidence as parts of such conceptual#R##N##R##N#knowledge, this way generating possible future developments. The experimental results show, among others,#R##N##R##N#the prediction of possible obstacle situations and their effect on the robot actions and estimated execution#R##N##R##N#times.
['Jos Lehmann', 'Bernd Neumann', 'Wilfried Bohlken', 'Lothar Hotz']
A Robot Waiter that Predicts Events by High-level Scene Interpretation