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

  • 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.

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Metadaten
Document Type:Conference Object
Language:English
Parent Title (English):Bicchi (Ed.): 2011 IEEE International Conference on Robotics and Automation (ICRA), 9-13 May 2011, Shanghai, China
First Page:3554
Last Page:3561
ISBN:978-1-61284-385-8
DOI:https://doi.org/10.1109/ICRA.2011.5980106
Publisher:IEEE
Date of first publication:2011/08/15
Note:
The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. FP7-ICT-231940-BRICS (Best Practice in Robotics).
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2015/04/02