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• W4285192725 endingPage "994" @default.
• W4285192725 startingPage "981" @default.
• W4285192725 abstract "Robust and highly accurate position estimation in underground mines is investigated by considering a vehicle equipped with 2D laser scanners. A survey of available methods to process data from such sensors is performed with focus on feature extraction methods. Pros and cons of the usage of different methods for the positioning application with 2D laser data are highlighted, and suitable methods are identified. Three state-of-the-art feature extraction methods are adapted to the scenario of positioning in a predefined map and the methods are evaluated through experiments conducted in a simulated underground mine environment. Results indicate that feature extraction methods perform in parity with the method of matching each ray individually to the map, and better than the point cloud scan matching method of a pure ICP, assuming a highly accurate map is available. Furthermore, experiments show that feature extraction methods more robustly handle imperfections or regions of errors in the map by automatically disregarding these regions." @default.
• W4285192725 created "2022-07-14" @default.
• W4285192725 creator A5001137240 @default.
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• W4285192725 date "2023-04-01" @default.
• W4285192725 modified "2023-10-17" @default.
• W4285192725 title "Survey on 2D Lidar Feature Extraction for Underground Mine Usage" @default.
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• W4285192725 doi "https://doi.org/10.1109/tase.2022.3172522" @default.
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