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14th European Conference on Product and Process Modelling, ECPPM 2022

作者： Pfitzner, F. Braun, A. Borrmann, A. Computational Modeling and Simulation Technical University of Munich Munich Germany

ISBN: (纸本)9781032406732

Data mining methods can invoke substantial optimization potential, as demonstrated in the manufacturing industry. Looking at the construction industry and precisely the as-performed stage, though, this research area is in its infancy worldwide. By now, it is not clear how specific on-site activities can be monitored adequately and how diverse data sources can be combined to make transparent and invulnerable statements about particular on-site activities. The presented study investigates the application of modern data analysis methods to ongoing construction projects to reveal information about specific activities. Raw data from various construction sites has been gained using camera systems, Bluetooth Low Energy (BLE) sensors, and laser scanners to build a powerful foundation of data sources. A pipeline for integrating different data sources has been developed to handle a large amount and variety of data and its subsequent processing into higher-level information. Using a data mining approach, namely map-reduce, we scaled the significant amount of data down to particular problem-targeted databases. Object detection methods were applied to process images of the construction activities. It was possible to detect on-site construction workers’ start and end times, breaks, and location. The introduced results have been verified by using fixed beacons and heterogeneous data types. In conclusion, the presented research provides fundamental methods for examining existing construction processes and collecting data for future analyses. © 2023 the Author(s).

关键词： Data mining

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360-Degree Tri-Modal Scanning: Engineering a Modular Multi-Sensor Platform for Semantic Enrichment of BIM Models

360-Degree Tri-Modal Scanning: Engineering a Modular Multi-S...

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2024 ISPRS Technical Commission I Mid-term Symposium on Intelligent Sensing and Remote Sensing Application

作者： Collins, Fiona C. Noichl, Florian Slepicka, Martin Cones, Gerda Borrmann, André Chair of Computational Modeling and Simulation School of Engineering and Design Technical University of Munich Munich80333 Germany

Point clouds, image data, and corresponding processing algorithms are intensively investigated to create and enrich Building Information Models (BIM) with as-is information and maintain their value across the building lifecycle. Point clouds can be captured using LiDAR and enriched with color information from images. Complementary to such dual-sensor systems, thermography captures the infrared light spectrum, giving insight into the temperature distribution on an object’s surface and allowing a diagnosis of the as-is energetic health of buildings beyond what humans can see. Although the three sensor modes are commonly used in pair-wise combinations, only a few systems leveraging the power of tri-modal sensor fusion have been proposed. This paper introduces a sensor system comprising LiDAR, RGB, and a radiometric thermal infrared sensor that can capture a 360-degree range through bi-axial rotation. The resulting tri-modal data is fused to a thermo-color point cloud from which temperature values are derived for a standard indoor building setting. Qualitative data analysis shows the potential for unlocking further object semantics in a state-of-the-art Scan-to-BIM pipeline. Furthermore, an outlook is provided on the cross-modal usage of semantic segmentation for automatic, accurate temperature calculations. © 2024 Fiona C. Collins et al.

关键词： Semantics

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Creating digital twins of existing bridges through AI-based methods

Creating digital twins of existing bridges through AI-based ...

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IABSE Symposium Prague 2022: Challenges for Existing and Oncoming Structures

作者： Mafipour, M. Saeed Vilgertshofer, Simon Borrmann, André Computational Modeling and Simulation Technical University of Munich Germany

ISBN: (纸本)9783857481833

Bridges require regular inspection and maintenance during their service life, which is costly and time-consuming. Digital twins (DT), which incorporate a geometric-semantic model of an existing bridge, can support the operation and maintenance process. The process of creating such DT models can be based on Point cloud data (PCD), created via photogrammetry or laser scanning. However, the semantic segmentation of PCD and parametric modeling is a challenging process, which is nonetheless necessary to support DT modeling. This paper aims to propose a segmentation method that is the basis for a parametric modeling approach to enable the semi-automatic geometric modeling of bridges from PCD. To this end, metaheuristic algorithms, fuzzy C-mean clustering, and signal processing algorithms are used. The results of this paper show that the scan to BIM process of bridges can be automated to a large extent and provide a model that meets the industry's demand. © 2022 IABSE Symposium Prague, 2022: Challenges for Existing and Oncoming Structures - Report. All rights reserved.

关键词： Semantics

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SLAM2REF: advancing long-term mapping with 3D LiDAR and reference map integration for precise 6-DoF trajectory estimation and map extension

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Construction Robotics 2024年第2期8卷 1-30页

作者： Vega-Torres, Miguel A. Braun, Alexander Borrmann, André Chair of Computational Modeling and Simulation Technical University of Munich Munich Germany

This paper presents a pioneering solution to the task of integrating mobile 3D LiDAR and inertial measurement unit (IMU) data with existing building information models or point clouds, which is crucial for achieving precise long-term localization and mapping in indoor, GPS-denied environments. Our proposed framework, SLAM2REF, introduces a novel approach for automatic alignment and map extension utilizing reference 3D maps. The methodology is supported by a sophisticated multi-session anchoring technique, which integrates novel descriptors and registration methodologies. Real-world experiments reveal the framework’s remarkable robustness and accuracy, surpassing current state-of-the-art methods. Our open-source framework’s significance lies in its contribution to resilient map data management, enhancing processes across diverse sectors such as construction site monitoring, emergency response, disaster management, and others, where fast-updated digital 3D maps contribute to better decision-making and productivity. Moreover, it offers advancements in localization and mapping research. Link to the repository: https://***/MigVega/SLAM2REF , Data: https://***/10.14459/2024mp1743877 .

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Digital Twinning in Additive Manufacturing - Closing the Digital-Physical-Digital Loop by Automated Integration of Captured Geometric Data into Fabrication Information Models 19th

Digital Twinning in Additive Manufacturing - Closing the Dig...

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19th International Conference on Computing in Civil and Building Engineering, ICCCBE 2022

作者： Slepicka, Martin Mawas, Karam Borrmann, André Maboudi, Mehdi Gerke, Markus Chair of Computational Modeling and Simulation Technical University of Munich Munich80333 Germany Institute of Geodesy and Photogrammetry Technische Universitaet Braunschweig Braunschweig38106 Germany

ISBN: (纸本)9783031353987

As part of the digitization of the AEC industry, the Digital Twin concept is becoming increasingly important. Originating in the manufacturing industry, the concept at its core involves a bidirectional coupling of the physical product and its digital counterpart with the aim of keeping the two in sync. Without appropriate capabilities to realize such synchronization, the concept always remained as an unattainable vision for the AEC industry. Adapting additive manufacturing (AM) for construction, however, creates unique opportunities to realize this vision by enabling automation in both directions, from digital to physical product and vice versa. As a fully automatable manufacturing method where robotic processes are typically controlled by the digital representation of the product, AM realizes the digital-to-physical link for this purpose. Conversely, based on the same digital representation of the product, the acquisition of the physical implementation of the manufacturing process can be automated, enabling the physical-to-digital connection. This paper uses three AM application scenarios to illustrate, on the one hand, the need for automating quality control and, on the other hand, to describe approaches for its realization. In particular, the benefits of synergy between automated quality control (QC) and fabrication information modeling (FIM) to form a digital-physical-digital loop are explored. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fabrication

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Automated Productivity Evaluation of Concreting Works: The Example of Concrete Pillar Production

Automated Productivity Evaluation of Concreting Works: The E...

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International Conference on Construction Logistics, Equipment, and Robotics, CLEaR 2023

作者： Pfitzner, Fabian Schlenger, Jonas Borrmann, André Chair of Computational Modeling and Simulation Technical University of Munich Munich Germany Leonhard Obermeyer Center TUM Center of Digital Methods for the Built Environment Munich Germany

ISBN: (纸本)9783031440205

Site schedules are usually developed by the rule of thumb based on the experience of on-site managers. While this approach can be suitable for smaller job sites, it is challenging to make good decisions for larger projects. Planning errors can result in massive delays and increasing costs. Significant improvements in other industries showed that data-driven productivity analysis of past processes advances the planning and execution of current and future projects. However, in the Architecture, Engineering & Construction (AEC) domain, automated productivity analysis of the construction phase has barely been investigated. To overcome this deficiency, this paper presents a first approach for multi-level productivity analysis of shell constructions. We discuss several state-of-the-art vision-based technologies that serve as a foundation for large-scale evaluation of the progress on a construction site. A complete pipeline is introduced that uses different types of neural networks to extract productivity information from images at various levels of detail. The proposed workflow is demonstrated for the construction process of cast-in-place concrete pillars, implementing the first two layers. Finally, remaining challenges are discussed. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data mining

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Multi-view KPConv for enhanced 3D point cloud semantic segmentation using multi-modal fusion with 2D images 14th

Multi-view KPConv for enhanced 3D point cloud semantic segme...

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14th European Conference on Product and Process Modelling, ECPPM 2022

作者： Du, C. Vega, M.A. Pan, Y. Borrmann, A. Computational Modeling and Simulation Technical University of Munich Munich Germany Institute for Advanced Study Technical University of Munich Munich Germany

ISBN: (纸本)9781032406732

Compared with unimodal deep learning algorithms that directly process 3D point clouds, multimodal fusion algorithms that leverage 2D images as supplementary information have performance advantages. In this work, the performance of an open-source multimodal algorithm, MVPNet, is improved on the 3D semantic segmentation task by using KPConv as a more robust 3D backbone. Different modules of the two networks are meaningfully combined: the 2D-3D lifting method provided by MVPNet aggregates selected 2D image features into 3D point clouds, then KPConv is used to fuse these features with geometric information to make predictions. On a ScanNet sub dataset, the proposed network significantly outperforms the original MVPNet and KPConv regardless of the fusion structure. By integrating COLMAP into the workflow, we further extend the proposed method to a custom dataset. The results show the improved performance of our multimodal fusion algorithm in identifying relevant categories of objects in the 3D scene. © 2023 the Author(s).

关键词： Semantic Segmentation

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A proposed IFC extension for timber construction buildings to enable acoustics simulation 14th

A proposed IFC extension for timber construction buildings t...

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14th European Conference on Product and Process Modelling, ECPPM 2022

作者： Châteauvieux-Hellwig, C. Abualdenien, J. Borrmann, A. Centre for Research Development and Technology Transfer Rosenheim Technical University of Applied Sciences Germany Computational Modeling and Simulation Technical University of Munich Germany

ISBN: (纸本)9781032406732

More and more architects and planners are choosing timber in construction because of its sustainability. However, timber elements have low mass, consist of multi-layered structures, and require complex junctions which makes the design process and construction challenging. The design of the junctions influences the sound insulation quality of a building and affects the quality of life for the inhabitants. To save time and cost, the detailed information on junctions should be included already in the early phases of the design process. In this paper, we present an improved building information modelling (BIM) workflow for timber construction. We develop new entities, relations, and property sets with detailed information on junctions that can be included in a BIM model using Industry Foundation Classes (IFC). These improvements will allow the designers to incorporate an acoustic data model that forms the basis for further prognoses of the airborne and impact sound insulation already in early design phases which in turn will reduce time and cost, and improve the quality of the design and the overall design process. © 2023 the Author(s).

关键词： Timber

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NUMERICAL FLOW VISUALIZATION: VISTA AND EXPEDITION

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Journal of Flow Visualization and Image Processing 2022年第3期29卷 1-27页

作者： Liu, Zhanping Department of Computational Modeling and Simulation Engineering Old Dominion University ODU-CMSE 1300 ECSB 4700 Elkhorn Avenue NorfolkVA23529 United States

Numerical flow visualization resorts to data processing, feature extraction, geometric construc-tion, image synthesis, graphical display, and scene manipulation to enable intuitive insightful interactive analysis of tangential directions of movement embedded in a velocity vector field. This paper presents some advances in numerical flow visualization over the past three decades, with emphasis on geometry-based and texture-based methods. Also introduced in this context is our own research for representing, depicting, and exploring flow data. Not intended for an exhaustive survey of the literature, our discussions revolve around streamline integration, interactive streamline placement, automatic streamline placement (including evenly spaced layout of streamlines), streamline clustering, time-dependent flow lines (e.g., pathlines), flow texture synthesis (e.g., line integral convolution), feature mining (e.g., flow topology), and parallel vi-sualization. These topics address flows ranging from planar to surface and volumetric domains, from steady to unsteady cases, and from Cartesian to curvilinear and unstructured grids. This scope allows us to examine a variety of approaches in the working mechanism, numerical accu-racy, representation effectiveness, visual quality, and computational performance so as to show the respective advantages and disadvantages. The findings may help visualization researchers pinpoint main long-lasting challenges, visualization developers identify practically applicable techniques, and domain scientists perceive important promising advances in numerical flow visualization. © 2022 by Begell House, Inc.

关键词： Textures

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BIM-SLAM: Integrating BIM Models in Multi-session SLAM for Lifelong Mapping using 3D LiDAR

arXiv

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arXiv 2024年

作者： Vega Torres, M.A. Braun, A. Borrmann, A. Chair of Computational Modeling and Simulation Technical University of Munich Munich Germany

While 3D Light Detection and Ranging (LiDAR) sensor technology is becoming more advanced and cheaper every day, the growth of digitalization in the Architecture, Engineering and Construction (AEC) industry contributes to the fact that 3D building information models (BIM models) are now available for a large part of the built environment. These two facts open the question of how 3D models can support 3D LiDAR long-term Simultaneous Localization and Mapping (SLAM) in indoor, Global Positioning System (GPS)-denied environments. This paper proposes amethodology that leveragesBIM models to create an updatedmapof indoor environments with sequential LiDAR measurements. Session data (pose graph-based map and descriptors) are initially generated from BIM models. Then, real-world data is aligned with the session data from the model using multi-session anchoring while minimizing the drift on the real-world data. Finally, the new elements not present in the BIM model are identified, grouped, and reconstructed in a surface representation, allowing a better visualization next to the BIM model. The framework enables the creation of a coherent map aligned with the BIM model that does not require prior knowledge of the initial pose of the robot, and it does not need to be inside the map. © 2024, CC BY.

关键词： Global positioning system

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