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Extraction of free-space structures for path planning purposes
2008 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

LKAB one of the world’s leading producers of upgraded iron ore products for the steel industry, uses autonomous Laud-Haul-Dump (LHD) machines for transportation of the iron ore at their underground mine located in Kiruna, Sweden. These machines are an essential part in the flow of ore transportation out of the mine and therefore the driving speed of these machines is very important. Today the drive paths for these machines are drawn by hand in computer software and this is a human-computer interaction that LKAB wants to remove because of the time consumption and also for the possibility to automatically generate faster and more optimized drive paths. Research has been conducted at Luleå University of Technology concerning optimization of drive paths for autonomous machines. This research resulted in a software prototype that integrated map-handling and path generation for the machines at LKAB. This prototype was based on a path generation algorithm with the unfortunately limitation of that the polygon must be monotone, and that is not the typical case for the drive paths that the machines are using. This thesis will show an implementation of an extension of this prototype that will improve the functionality so that polygons without constraints can be used in the calculations of optimized drive paths. In order to achieve this result triangulation of polygons and breadth first search has been used. Due to safety precautions a margin from the wall must exist on each side of the drive path to prevent the machine from colliding with the walls, this will affect the size of the polygon and the recalculation of the polygon is described in this thesis. It will show how optimizations for the inner and outer curves on the drive path will affect the final result of the optimization.

Place, publisher, year, edition, pages
Keyword [en]
Technology, Geometric algorithms
Keyword [sv]
URN: urn:nbn:se:ltu:diva-50847ISRN: LTU-EX--08/051--SELocal ID: 8116710d-21e8-4a69-aa75-22f6988c2017OAI: diva2:1024210
Subject / course
Student thesis, at least 30 credits
Educational program
Computer Science and Engineering, master's level
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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