Authors:
Jos Lehmann
;
Bernd Neumann
;
Wilfried Bohlken
and
Lothar Hotz
Affiliation:
University of Hamburg, Germany
Keyword(s):
Prediction, Ontology, High-level Robotics.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Cognitive Robotics
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Enterprise Ontologies
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Knowledge Representation and Reasoning
;
Model-Based Reasoning
;
Ontologies
;
Physical Agents
;
Robot and Multi-Robot Systems
;
Robotics and Automation
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
Being able to predict events and occurrences which may arise from a current situation is a desirable capability
of an intelligent agent. In this paper, we show that a high-level scene interpretation system, implemented as
part of a comprehensive robotic system in the RACE project, can also be used for prediction. This 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 possible
occurrences and courses of action, e.g. when serving a coffee to a guest. Our approach requires that 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 knowledge
may be acquired by conceptualizing experiences collected in the robot’s memory. Predictions are generated
by a model-construction p
rocess which seeks to explain evidence as parts of such conceptual knowledge, this
way generating possible future developments. The experimental results show, among others, the prediction of
possible obstacle situations and their effect on the robot actions and estimated execution times.
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