Title
A robotic knowledge base to model and update real-world information from indoor environments
Author
Sijs, J.
Fletcher, J.
Publication year
2022
Abstract
Robotic systems operating in the real world would benefit from a clear semantic model to understand their interactions with the real world. Such semantics are typically captured in an ontology. Unfortunately, the underlying model of existing ontologies requires many work-arounds before it can be used to capture general knowledge about objects and interactions in the real physical world. To remove such work-arounds, this article adopts the richer hypergraph model. It is used to develop an ontology, which is further implemented as the knowledge base of an actual robotic system performing search operations. Also, actual information extracted from the robot’s sensors is used to update its knowledge base logically and sensibly.
Subject
Ontology
Knowledge base
Sensor observations
To reference this document use:
http://resolver.tudelft.nl/uuid:68214490-0d2e-4c84-9a73-16d0ff2fc53c
TNO identifier
977867
Publisher
IEEE
Source
25th International Conference on Information Fusion (FUSION)
Document type
conference paper