Indoor multi-level semantic topological index construction method for complex navigation application

Abstract

The invention provides an indoor multi-level semantic topological index construction method for complex navigation application. The method comprises the following steps: acquiring a live-action three-dimensional model of a target complex, and synchronously matching a corresponding relationship between semantic and geometric components in a space building object to obtain an indoor unit model with complete topological consistency; extracting passable areas, and abstracting the passable areas as leaf nodes; constructing a scene similarity-oriented multi-dimensional correlation function, and performing grouping processing on the leaf nodes to generate an aggregation unit; and splitting and superposing the interiors of the aggregation units to obtain a connection relationship between the indoor unit models and a connection relationship between the aggregation units, and constructing a connectivity graph index from inside to outside. In this way, the problem that the communication relation expressed by a single topological structure is disordered can be solved, the logical relation of indexes can be simplified, and the time efficiency and accuracy of target searching in a path planning task are improved.

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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