Accurate positioning model of urban underground pipelines based on BIM technology and graph optimization algorithm

Abstract

Urban underground pipelines are a critical part of infrastructure systems in modern cities. Traditional underground pipeline positioning methods often exhibit poor accuracy and low robustness due to environmental interference, material diversity, and spatial complexity. To address these issues, this study proposes a precise positioning model that integrates Building Information Modeling (BIM) technology with a graph-based optimization approach. The model fuses data from inertial measurement units and odometers, introduces modules for error compensation and pre-integration, and embeds spatial constraints extracted from BIM to suppress positioning drift. A revisit detection mechanism based on trajectory waveform similarity is also designed to enhance long-term accuracy. Experimental results based on a public underground utility dataset show that the proposed model achieves a positioning accuracy of 95.6 percent, an average error of 0.45 m, and a time efficiency of 0.9 s. It also demonstrates a detection coverage rate of 96.3 percent, a revisit detection accuracy of 89.7 percent, and a cumulative error drift reduced to 0.32 m per kilometer. Compared to traditional and partially optimized methods, the proposed model significantly improves both localization precision and trajectory consistency. The visualized trajectory results further confirm the positive impact of BIM constraints on spatial correction. Overall, the model provides a practical and scalable solution for high-precision underground pipeline localization in complex urban environments.

Keywords

BIM / Graph optimization algorithm / Urban planning / Underground pipelines / Location

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