Merfels, Christian (2014)
Large-scale probabilistic feature mapping and tracking for autonomous driving.
Technische Universität
Master Thesis, Primary publication
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M.Sc. Computer Science thesis -
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Item Type: | Master Thesis | ||||
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Type of entry: | Primary publication | ||||
Title: | Large-scale probabilistic feature mapping and tracking for autonomous driving | ||||
Language: | English | ||||
Referees: | Peters, Prof. Dr. Jan | ||||
Date: | 22 May 2014 | ||||
Place of Publication: | Darmstadt | ||||
Date of oral examination: | 23 July 2014 | ||||
Abstract: | Autonomous driving requires a precise vehicle localization which can be achieved by using specific maps. This creates the challenge of constructing a system that generates these maps at a large scale by fusing sensor data. The issue of producing maps was in a previous project addressed by a cumbersome and error-prone manual process which only yielded feature-based maps. The approach of this thesis is to fuse sensor data and automatically create grid- and feature-based maps with a novel integrated technique. For this purpose, a software system called gridmap is developed and a supplementary analysis framework for the resulting maps is established. This software is being used in autonomous driving projects for grid- and feature-based localization approaches in the U.S. and in Germany. |
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URN: | urn:nbn:de:tuda-tuprints-41122 | ||||
Divisions: | 20 Department of Computer Science > Intelligent Autonomous Systems | ||||
Date Deposited: | 14 Aug 2014 11:38 | ||||
Last Modified: | 09 Jul 2020 00:46 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/4112 | ||||
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