Learning spatial relations between objects from 3D scenes

Severin Fichtl, John Alexander, Frank Guerin, Wail Mustafa, Dirk Kraft, Norbert Kruger

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

1 Citation (Scopus)

Abstract

In this work, we learn a limited number of abstractions which can then be used to form preconditions for motor actions. These abstractions take the form of spatial relations amongst objects. We consider three “classes” of spatial relation: The objects either are separated from, on-top of, or inside each other. We have tackled this same problem in previous work (Fichtl et al., 2013). Here we report on recent improved results using a novel application of histograms to visually recognise a spatial relation between objects in the environment. Using this histogram based approach we are able to report a very high rate of success when the system is asked to recognise a spatial relation.
Original languageEnglish
Title of host publication2013 IEEE 3rd Joint International Conference on Development and Learning and Epigenetic Robotics, ICDL 2013 - Electronic Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-2
Number of pages2
ISBN (Electronic)9781479910366
DOIs
Publication statusPublished - 2013
Event2013 IEEE 3rd Joint International Conference on Development and Learning and Epigenetic Robotics, ICDL 2013 - Osaka, Japan
Duration: 18 Aug 201322 Aug 2013

Conference

Conference2013 IEEE 3rd Joint International Conference on Development and Learning and Epigenetic Robotics, ICDL 2013
Country/TerritoryJapan
CityOsaka
Period18/08/1322/08/13

Bibliographical note

This work was supported by the EU Cognitive Systems project XPERIENCE (FP7-
ICT-270273) and Leverhulme Grant F/00 152/AL

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