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Towards identification of best practice algorithms in 3D perception and modeling

 
: Blumenthal, Sebastian; Fischer, Jan; Nowak, Walter; Prassler, Erwin

:
Preprint urn:nbn:de:0011-n-1849815 (140 KByte PDF)
MD5 Fingerprint: 106507d23487234c35104d41ef31beb4
© 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Erstellt am: 19.11.2011


IEEE Robotics and Automation Society; Shanghai Jiao Tong University:
IEEE International Conference on Robotics and Automation, ICRA 2011. DVD : Better Robots, Better Life. May 9-13, 2011, Shanghai, China; Workshop Semantic Perception, Mapping and Exploration (SPME)
New York, NY: IEEE, 2011
ISBN: 978-1-61284-380-3
S.3554-3561
International Conference on Robotics and Automation (ICRA) <2011, Shanghai>
Workshop Semantic Perception, Mapping and Exploration (SPME) <2011, Shanghai>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPA ()
3D-Bildverarbeitung; Best Practice; Navigation; Algorithmus; Bildverarbeitung; Objekterkennung; Software

Abstract
Robots need a representation of their environment to reason about and to interact with it. Different 3D perception and modeling approaches exist to create such a representation, but they are not yet easily comparable. This work tries to identify best practice algorithms in the domain of 3D perception and modeling with a focus on environment reconstruction for robotic applications. The goal is to have a collection of refactored algorithms that are easily measurable and comparable. The realization follows a methodology consisting of five steps. After a survey of relevant algorithms and libraries, common representations for the core data-types Cartesian point, Cartesian point cloud and triangle mesh are identified for use in harmonized interfaces. Atomic algorithms are encapsulated into four software components: the Octree component, the Iterative Closest Point component, the k-Nearest Neighbors search component and the Delaunay triangulation component. A sample experiment demonstrates how the component structure can be used to deduce best practice.

: http://publica.fraunhofer.de/dokumente/N-184981.html