Planar segmentation for Geometric Reverse Engineering using data from a laser profile scanner mounted on an industrial robot
2008 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]
Laser scanners in combination with devices for accurate orientation like Coordinate Measuring Machines (CMM) are often used in Geometric Reverse Engineering (GRE) to measure point data. The industrial robot as a device for orientation has relatively low accuracy but the advantage of being numerically controlled, fast, flexible, rather cheap and compatible with industrial environments. It is therefore of interest to investigate if it can be used in this application.
This thesis will describe a measuring system consisting of a laser profile scanner mounted on an industrial robot with a turntable. It will also give an introduction to Geometric Reverse Engineering (GRE) and describe an automatic GRE process using this measuring system. The thesis also presents a detailed accuracy analysis supported by experiments that show how 2D profile data can be used to achieve a higher accuracy than the basic accuracy of the robot. The core topic of the thesis is the investigation of a new technique for planar segmentation. The new method is implemented in the GRE system and compared with an implementation of a more traditional method.
Results from practical experiments show that the new method is much faster while equally accurate or better.
Place, publisher, year, edition, pages
Örebro: Örebro universitet , 2008. , p. 31
Series
Studies from the Department of Technology at Örebro University, ISSN 1404-7225 ; 30
Keywords [en]
Geometric Reverse Engineering, 3D measurement systems, laser scanner, planar segmentation, region-growing
National Category
Information Systems
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-2318OAI: oai:DiVA.org:oru-2318DiVA, id: diva2:136114
Presentation
2008-06-11, T131, Teknikhuset, Fakultetsgatan 1, Örebro, 13:00 (English)
Opponent
Supervisors
2008-06-112008-06-112018-01-13Bibliographically approved
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