Development of Semantic BIM for Supporting UAV-Based Reality Capture for Facilities Management Applications

开发语义 BIM，支持设施管理应用中基于无人机的现实捕捉

• 批准号: 521798-2017
• 负责人: Hammad, Amin
• 金额: $ 1.82万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=639605
• 关键词: Development; Semantic; BIM; Supporting; UAV

Reality capture (RC) of constructed facilities (e.g. buildings) is an important step towards developing reliableas-is models that can be used for facilities management. Traditionally, these models are developed based ondesign drawings and/or surveying data of the facilities. However, design drawings of existing facilities may bemissing or not reflecting the actual conditions of the facilities because of accumulated deterioration or becauseof maintenance and renovation activities that were not documented. On the other hand, conventional surveyingmethods are expensive, time consuming, and may not be safe in some cases (e.g. post-disaster inspection).Pegasus Research & Technologies (PRT) provides research and engineering services to the Canadian aerospaceand defense sector, such as simulation test-bed for Unmanned Aerial Vehicles (UAV) experimentation usingartificial intelligence. Recently, the service offering of PRT has grown to include RC for buildings facilitiesmanagement applications using a laser scanner mounted on the UAV. However, transforming the data collectedby the scanner to a useful Building Information Model (BIM) is a challenging task.This project assumes that a UAV equipped with a laser scanner is used for collecting the data needed forcreating a 3D model of the interior spaces in a building. Furthermore, it assumes that there is an algorithm forobject recognition/classification based on the sensory data collected by the UAV. The results of the recognitionare building components (e.g. wall, window, door, etc.) that are already defined in a semantic map. However, agap in this area is that there is currently no direct way of linking this semantic map with BIM. The project aimsto: (1) develop an interface between the semantic map and standard BIM classes; and (2) automatically create aBIM model based on the collected data in order to support the subsequent building inspection tasks.

构造设施（例如，建筑物）的现实捕获（RC）是开发可用于设施管理的Reliableas-IS模型的重要步骤。传统上，这些模型是基于设计图纸和/或设施的测量数据开发的。但是，由于累积的恶化或由于未记录的维护和翻新活动，现有设施的设计图可能会感到困惑或不反映设施的实际条件。另一方面，传统的测量方法很昂贵，耗时，在某些情况下可能不安全（例如，降水后检查）。PegasusResearch＆Technologies（PRT）为加拿大航空航空公司的国防部门提供了研究和工程服务，例如使用Airnealnennenned Veasiles（UAV）使用一员的人工智能进行模拟测试。最近，PRT的服务产品已逐渐增加，包括使用无人机上安装的激光扫描仪的建筑物设施管理应用程序的RC。但是，将扫描仪收集的数据转换为有用的建筑信息模型（BIM）是一项具有挑战性的任务。本项目假设配备了激光扫描仪的无人机用于收集建筑物中内部空间的3D模型所需的数据。此外，它假定基于无人机收集的感官数据存在算法forobject识别/分类。在语义图中已定义的识别式建筑组件（例如墙，窗户，门等）的结果。但是，该领域的AGAP是目前尚无将该语义图与BIM联系起来的直接方法。项目AIMSTO：（1）在语义图和标准BIM类之间开发一个接口； （2）基于收集的数据自动创建ABIM模型，以支持后续的建筑物检查任务。