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Automation of Inspection Mission Planning Using 4D BIMs and in Support of Unmanned Aerial Vehicle-Based Data Collection

TitleAutomation of Inspection Mission Planning Using 4D BIMs and in Support of Unmanned Aerial Vehicle-Based Data Collection
Publication TypeJournal Article
Year of Publication2021
AuthorsHamledari, H, Sajedi, SOmid, McCabe, B, Fischer, M
JournalASCE Journal of Construction Engineering and Management
Keywords4D, Automation, BIM, Construction, progress tracking, Robotics, UAV
Abstract

The data collected by unmanned aerial vehicles (UAV) provide unique opportunities for applications, such as construction progress tracking and facility monitoring. To increase the effectiveness of UAV-captured data, inspection mission plans should be designed prior to site visits. The data collection locations must be identified and adjusted based on the user’s objectives. The UAV flight mission must guarantee a visit to each identified location, and the inspection plans must satisfy the constraints imposed by safety requirements, no-fly zones, and UAV’s limited battery life. This problem becomes more complicated indoors due to complex and continuously changing building layouts. This work uses four-dimensional (4D) building information models (BIM) to automatically design optimal UAV mission plans in support of indoor UAV-enabled data acquisition. It automatically identifies the inspection targets based on users’ customizable and multicriteria description of objectives (e.g., columns behind schedule). The three-dimensional (3D) navigable space is automatically calculated by time stamping the 4D models based on the inspection date. The navigable space is further refined based on safety rules. An optimal UAV inspection mission plan is developed using swarm intelligence that ensures complete coverage of targets and minimizes battery use. The method is based on the industry foundation classes (IFC) schema, promoting OpenBIM and interoperability, which are core challenges in the construction information modeling domain.

URLhttps://doi.org/10.1061/(ASCE)CO.1943-7862.0001995