Robot Vision Applications using the CSEM SwissRanger Camera

AbstractThe SwissRanger is new type of depth vision camera using the Time-of-Flight (TOF) principle. It acquires in real time both normal intensity images and 3D range images. It is an active range finder with a harmless light source emitting near infrared light at under {1W}. Most other active range finders are laser based and have much higher latency. The SwissRangers usefulness is proved here by solving two diverse robot vision applications: The mobile robot localization problem and the 3D object pose estimation problem.
The robots localization is found by segmenting range images; into planar surfaces. The segmentation is done by calculating the local surface normals at each pixel, grouping the image into regions and robustly fittting to planes using {RANSAC}. From these planes a map of the robots environment is constructed. For a robot to handle an object it has to recognize the objects pose or orientation in space. This is approached by using a dimensionality reduction method called Local Linear Embedding (LLE). A dataset, with range images of an object can be seen as points in a very high dimensional pixel space. It has been shown that for {3D} objects such points lie on nonlinear manifolds in the high dimensional space. The {LLE} technique reduces the dimensionality down to a true dimensionality of the manifold and reveals the separating characteristic in each point namely its pose. The pose of a new objects can then be detected by mapping it to this low dimensional space.
Keywordsmathematical modelling, 3D imaging, time-of-flight, range images, robot localization, pose estimation, range image segmentation, non-linear dimension reduction, Local Linear Embedding
TypeMaster's thesis [Academic thesis]
Year2006    Month August    pp. 99    Ed. 1
PublisherInformatics and Mathematical Modelling, Technical University of Denmark,DTU
ISBN / ISSN87-643-0095-1
NoteSupervised Rasmus Larsen, and co-supervisor Jens Michael Carstensen, {IMM}.
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Image Analysis & Computer Graphics