Application of SLAM Algorithm in The Construction of 2-D Maps
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Abstract
In today's society, maps, as an important tool for human spatial cognition and spatial thinking, solidify and abstract the results of spatial cognition to complete the visual expression and information transmission of geographic information, and provide auxiliary decision-making for people to understand the urban pattern, formulate travel routes, take a taxi or self-drive navigation and other geospatial activities. The role of this is obvious, human beings have more strict requirements for maps, and the algorithms that can draw maps are also blooming. The purpose of this paper is to study the application of SLAM algorithm in the construction of simple 2-D maps, analyze the advantages of SLAM algorithm in the construction of 2-D maps, and analyze the role of closed-loop detection and trajectory optimization in the process of building 2-D maps. SLAM includes lidar data mapping, which has high measurement accuracy and stable measurement performance, and is now more widely used in industry.
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