Learning Spatial Relationships From 3D Vision Using Histograms

Severin Andreas Fichtl, Andrew McManus, Wail Mustafa, Dirk Kraft, Norbert Krüger, Frank Guerin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Effective robot manipulation requires a vision system which can extract features of the environment which determine what manipulation actions are possible. There is existing work in this direction under the broad banner of recognising “affordances”. We are particularly interested in possibilities for actions afforded by relationships among pairs of objects. For example, if an object is “inside” another or “on top” of another. For this there is a need for a vision system which can recognise such relationships in a scene. We use an approach in which a vision system first segments an image, and then considers a pair of objects to determine their physical relationship. The system extracts surface patches for each object in the segmented image, and then compiles various histograms from looking at relationships between the surface patches of one object and those of the other object. From these histograms a classifier is trained to recognise the relationship between a pair of objects. Our results identify the most promising ways to construct histograms in order to permit classification of physical relationships with high accuracy. This work is important for manipulator robots who may be presented with novel scenes and must identify the salient physical relationships in order to plan manipulation activities.
Original languageEnglish
Title of host publication2014 IEEE International Conference on Robotics and Automation (ICRA)
PublisherIEEE Press
Pages501-508
Number of pages7
ISBN (Print)9781479936861
DOIs
Publication statusPublished - 1 May 2014
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: 31 May 20147 Jun 2014

Publication series

Name
ISSN (Print)1050-4729

Conference

Conference2014 IEEE International Conference on Robotics and Automation, ICRA 2014
CountryChina
CityHong Kong
Period31/05/147/06/14

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