Scene learning, recognition and similarity detection in a fuzzy ontology
  via human examples
  This paper introduces a Fuzzy Logic framework for scene learning, recognition
and similarity detection, where scenes are taught via human examples. The
framework allows a robot to: (i) deal with the intrinsic vagueness associated
with determining spatial relations among objects; (ii) infer similarities and
dissimilarities in a set of scenes, and represent them in a hierarchical
structure represented in a Fuzzy ontology. In this paper, we briefly formalize
our approach and we provide a few use cases by way of illustration.
Nevertheless, we discuss how the framework can be used in real-world scenarios.
