Indoor multi-level semantic topology index construction method for complex navigation applications

Abstract

The invention provides an indoor multi-level semantic topology index construction method for complex navigation applications. The method includes acquiring a real three-dimensional model of the target complex, synchronously matching the corresponding relationship between the semantic and geometric components in the spatial building object, and obtaining an indoor unit model with complete topological consistency; extracting the passable area, and abstracting the passable area as Leaf nodes; build a multi-dimensional correlation function oriented to scene similarity, group the leaf nodes to generate aggregate units; split and superimpose the inside of the aggregate units to obtain the indoor unit model and indoor unit model The connectivity relationship and the connection relationship between aggregated units are constructed from the inside to the outside of the connectivity graph index. In this way, it can make up for the disordered connection relationship expressed by a single topology structure, simplify the logical relationship of the index, and improve the time efficiency and accuracy of the target search in the path planning task.

Description

technical field [0001] Embodiments of the present invention generally relate to the technical field of geospatial data processing, and more specifically, relate to an indoor multi-level semantic topology index construction method for complex navigation applications. Background technique [0002] A complex complex is a large-scale, large-volume, highly comprehensive building with a complex and unified multi-equipment system. The center presents a nested distribution and some boundaries are staggered and twisted together, resulting in a variety of real-world models; ②The phenomenon of interpenetration between floors and interpenetration with external buildings, and a large indoor passage space, forming redundant redundancy ③ The functional diversity of indoor buildings leads to the explosive growth of indoor POI information, overflowing with a large amount of disorganized semantic data. Therefore, navigation applications for complex complexes still face great challenges in mo...

AI Technical Summary

Problems solved by technology

This scheme takes into account the effective association expression and multi-level data organization of indoor scene semantics, and solves the problem of insufficient connectivity relationship expressed by a single topology structure, as well as information mismatch caused by numerous models, redundant connectivity relationships, and semantic clutter in complex complexes. Problems such as low efficiency and high storage complexity

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