@inproceedings{DieckhoffBarliebGrothetal., author = {Dieckhoff, Christina and Barlieb, Christophe and Groth, Christian and Linner, Thomas and Weininger, Florian}, title = {Erfolgsfaktor Interdisziplinarit{\"a}t: Das Lehrformat Digitalisierungskollegs an Bayerischen Hochschulen}, series = {Informatik 2023 : Designing Futures: Zuk{\"u}nfte gestalten ; Tagung vom 26.-29.2023, Berlin}, booktitle = {Informatik 2023 : Designing Futures: Zuk{\"u}nfte gestalten ; Tagung vom 26.-29.2023, Berlin}, publisher = {Gesellschaft f{\"u}r Informatik e.V.}, isbn = {978-3-88579-731-9}, issn = {1617-5468}, doi = {10.18420/inf2023_22}, pages = {241 -- 252}, abstract = {Um den zunehmenden Anforderungen an die Beherrschung digitaler Techniken und an die F{\"a}higkeit zur interdisziplin{\"a}ren Zusammenarbeit an Studierende aller Fachrichtungen zu begegnen wurde das interdisziplin{\"a}re Lehrformat Digitalisierungskollegs f{\"u}r Studierende entwickelt. Das in vielen Fachbereichen ausbauf{\"a}hige Angebot von Digitalthemen in der Hoch- schullehre wird hiermit dauerhaft erweitert. Ein Digitalisierungskolleg besteht aus einer Vorlesungs- reihe mit angrenzendem Seminar, in denen Studierende interdisziplin{\"a}re L{\"o}sungen f{\"u}r Fragen der digitalen Transformation entwickeln. Geleitet werden sie von etablierten Wissenschaftlerinnen und Wissenschaftlern, aktiv betreut und ausgestaltet von ein bis zwei Coaches. Kernelement sowohl des Kollegs als auch der einzelnen Projekte ist die Interdisziplinarit{\"a}t. Eine*r der beteiligten Projekt- leiter*innen hat einen direkten Bezug zur Technik und kommt aus der Informatik, der Wirtschafts- informatik, der Elektrotechnik oder vergleichbaren Disziplinen. Zielgruppe der Projekte sind Studierende verschiedener Disziplinen im Masterstudium oder in den letzten Semestern eines Bachelorstudiums. Durch die Teilnahme erwerben auch Studierende aus digitalisierungsfernen F{\"a}chern fr{\"u}hzeitig umfangreiche IT-Kenntnisse. Als Begleiteffekt der umfangreichen Vernetzung zwischen den Digitalisierungskollegs (Studierende, Coaches und Projektleitende) entsteht bereits zu Beginn einer wissenschaftlichen Karriere eine große digitale Community. Alle Teilnehmenden lernen fr{\"u}hzeitig die interdisziplin{\"a}re Zusammenarbeit und verbessern erheblich ihre Karriere- chancen innerhalb und außerhalb der Wissenschaft.}, language = {de} } @inproceedings{SaffertSchmailzlSpitzhirnetal., author = {Saffert, Anne-Sophie and Schmailzl, Marc and Spitzhirn, Michael and Linner, Thomas}, title = {A Cyber-Physical Toolbox for Teaching Digital Construction - Technical Configuration, Learning Tactics and Hands-On Testing and Evaluation in Dedicated Courses}, series = {Learning Factories of the Future, Proceedings of the 14th Conference on Learning Factories 2024, Volume 2}, booktitle = {Learning Factories of the Future, Proceedings of the 14th Conference on Learning Factories 2024, Volume 2}, publisher = {Springer Nature}, address = {Cham}, isbn = {9783031653995}, issn = {2367-3370}, doi = {10.1007/978-3-031-65400-8_10}, pages = {83 -- 91}, abstract = {The construction industry faces substantial economic, environmental, and social challenges. Simultaneously, the industry experiences one of the lowest degrees of digitalization. In this context, cyber-physical education is essential to empower learners with skills to utilize digital and physical solutions more effectively. Therefore, a modular as well as construction specific learning setting was designed. The setting facilitates a range of topics, such as production planning considering human and robot capabilities, (semi-) automated construction machines, robotics, sensing \& actuation and more. The digital part of the cyber-physical toolbox consists of various methods and tools to learn programming languages, frameworks, offline simulators, post-processors and more. This step is essential to enable an end-to-end data-/workflow from design (e.g., BIM-based planning methodologies) to (machine-based) production. A focus is given to human-machine/-robot collaboration and appropriate simulation tools (e.g., emaWD) enabling the incorporation of human factors. The physical setting is highly modular, and each device and its periphery can be customized to a broad variety of learning scenarios and levels. This paper describes the details of the learning setting, extracts learning strategies, and analyzes selected learning scenarios and their initial testing in various learning formats.}, language = {en} } @inproceedings{EderHoengSchmailzletal., author = {Eder, Friedrich and Hoeng, Simon Konrad and Schmailzl, Marc and Linner, Thomas and Obergrießer, Mathias}, title = {Towards improving data interoperability for the reconstruction of existing buildings}, series = {The 20th conference of the International Society for Computing in Civil and Building Engineering (ICCCBE 2024), August 25 to 28, 2024, Montreal}, booktitle = {The 20th conference of the International Society for Computing in Civil and Building Engineering (ICCCBE 2024), August 25 to 28, 2024, Montreal}, abstract = {Digital representations of buildings are the supporting structures of various use-cases in the emerging field of data-driven decision making. From large scale applications in the context of city planning to the detailed evaluation of critical infrastructure they enable specialists to observe problems, interpret relationships, test solutions virtually and apply them in the real world. This is only feasible if the individual underlying digital model meets the requirements imposed by the analysis at hand. In practice, especially models of existing buildings are not easy to come by as the information describing the existing structure is often scattered across multiple different data sources in various formats. Previous research efforts have outlined methodologies which leverage machine learning, computer vision and subsequent semantic enrichment in order to achieve the (re)construction of such building models. However, these methods are generally not integrated with each other, nor do they consider being able to interface with a shared repository of building related data. In this paper we present a methodology which focuses on establishing a common context for all building related data by utilizing the Industry Foundation Classes (IFC) schema. In particular we focus on utilizing readily available geometric and semantic data originating from geographic information systems as a basis, subsequently referencing additional data sources in their corresponding context and finally outlining interfaces with downstream enrichment processes in both directions. Through incorporating contextualized (IFC) data into the early stages of the remodeling workflow, we outline an end-to-end process from the initial component-based data-acquisition to the as-built building information model. In establishing a standardized foundation for data exchange and collaboration it enables all stakeholders to work more seamlessly across different stages of the remodeling project.}, language = {en} } @inproceedings{SchmailzlSaffertKaramaraetal., author = {Schmailzl, Marc and Saffert, Anne-Sophie and Karamara, Merve and Linner, Thomas and Eder, Friedrich and Hoeng, Simon Konrad and Obergriesser, Mathias}, title = {Enhancing Decision-Making for Human-Centered Construction Robotics: A Methodological Framework}, series = {Proceedings of the 41st International Symposium on Automation and Robotics in Construction (ISARC), Lille, France}, booktitle = {Proceedings of the 41st International Symposium on Automation and Robotics in Construction (ISARC), Lille, France}, publisher = {International Association for Automation and Robotics in Construction (IAARC)}, isbn = {978-0-6458322-1-1}, issn = {2413-5844}, doi = {10.22260/ISARC2024/0083}, pages = {637 -- 644}, abstract = {While the Architecture, Engineering, and Construction (AEC) industry is increasingly aware of the rising demands for productivity and human-centered construction improvements, the holistic adoption of robotics as a fundamental strategy to address these challenges has not yet reached comprehensive fruition. This paper therefore introduces a methodological framework aiming to address the industry's pressing need for a systematic approach for assessing the feasibility of integrating robotics into human-centered construction processes. It aims to enhance decision-making regarding the degree of automation in human-centered construction processes, ranging from partial to full robotization or non-robotization. The framework is characterized by a more holistic end-to-end data-/workflow and therefore adopts a multifaceted approach, leveraging BIM-based planning methodologies and integrating new technologies [e.g., Motion Capturing (MoCap), work process simulation software incorporating Digital Human Models (DHM), self-developed conversion/interfacing software and more] that have not been widely used in the industry to date. Subsequently, the framework is evaluated in a real-life bricklaying construction process to ensure a more application-based approach. Overall, the framework advances current construction processes with a more inclusive and conscious technology infill to empower construction professionals with the workflow and corresponding tools necessary for the practical integration of robotics into human-centered construction processes.}, language = {en} } @inproceedings{SchmailzlSaffertKaramaraetal., author = {Schmailzl, Marc and Saffert, Anne-Sophie and Karamara, Merve and Linner, Thomas and Eder, Friedrich and Hoeng, Simon Konrad and Obergrießer, Mathias}, title = {Enhancing Decision-Making for Human-Centered Construction Robotics: A Methodological Framework}, series = {Proceedings of the 41st International Symposium on Automation and Robotics in Construction (ISARC 2024), 2024, Lille, France}, booktitle = {Proceedings of the 41st International Symposium on Automation and Robotics in Construction (ISARC 2024), 2024, Lille, France}, publisher = {IAARC}, isbn = {978-0-6458322-1-1}, doi = {10.22260/ISARC2024/0083}, pages = {637 -- 644}, abstract = {While the Architecture, Engineering, and Construction (AEC) industry is increasingly aware of the rising demands for productivity and human-centered construction improvements, the holistic adoption of robotics as a fundamental strategy to address these challenges has not yet reached comprehensive fruition. This paper therefore introduces a methodological framework aiming to address the industry's pressing need for a systematic approach for assessing the feasibility of integrating robotics into human-centered construction processes. It aims to enhance decision-making regarding the degree of automation in human-centered construction processes, ranging from partial to full robotization or non-robotization. The framework is characterized by a more holistic end-to-end data-/workflow and therefore adopts a multifaceted approach, leveraging BIM-based planning methodologies and integrating new technologies [e.g., Motion Capturing (MoCap), work process simulation software incorporating Digital Human Models (DHM), self-developed conversion/interfacing software and more] that have not been widely used in the industry to date. Subsequently, the framework is evaluated in a real-life bricklaying construction process to ensure a more application-based approach. Overall, the framework advances current construction processes with a more inclusive and conscious technology infill to empower construction professionals with the workflow and corresponding tools necessary for the practical integration of robotics into human-centered construction processes.}, language = {en} } @inproceedings{HoengWiedererEderetal., author = {H{\"o}ng, Simon K. and Wiederer, Jonas and Eder, Friedrich and Obergriesser, Mathias and Linner, Thomas}, title = {Towards AI-enhanced facade planning : integrating human expertise with machine learning-driven parametric modeling}, series = {EC³ \& CIB W78 : 2025 European Conference on Computing in Construction \& 42nd CIB W78 IT in Construction Conference}, volume = {6}, booktitle = {EC³ \& CIB W78 : 2025 European Conference on Computing in Construction \& 42nd CIB W78 IT in Construction Conference}, publisher = {European Council for Computing in Construction}, isbn = {978-9-083451-31-2}, issn = {2684-1150}, doi = {10.35490/EC3.2025.320}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-84862}, pages = {192 -- 199}, abstract = {Planning modern facade systems is complex, requiring optimization across multiple domains.This paper proposes an AI-enhanced workflow for facade planning, harnessing computer vision and human input via a Large Language Model.A generative AI system then guides a parametric model to produce 3D facade designs. Automated checks provide feedback to a Reinforcement Learning system, to iteratively determine optimal solutions.These solutions are verified and finalized by human expertise, ensuring improved outcomes with reduce planning time and effort.The approach illustrates how combining advanced AI methods with human expertise can address the multifactorial challenges of facade design within current industry practices.}, language = {en} } @inproceedings{SaffertWiedererHoengetal., author = {Saffert, Anne-Sophie and Wiederer, Jonas and H{\"o}ng, Simon and Linner, Thomas and Obergrießer, Mathias and Neumann, Patrick}, title = {Towards AI-based optimization of human-centered and robot-assisted construction processes}, series = {Proceedings of the 42nd International Symposium on Automation and Robotics in Construction (ISARC), Montreal, Canada July 28-31, 2025}, booktitle = {Proceedings of the 42nd International Symposium on Automation and Robotics in Construction (ISARC), Montreal, Canada July 28-31, 2025}, publisher = {IAARC}, isbn = {978-0-6458322-2-8}, issn = {2413-5844}, doi = {10.22260/ISARC2025/0112}, pages = {861 -- 868}, abstract = {This research explores an innovative AI-driven approach to optimizing construction processes with a focus on humancentered design, addressing key challenges in the construction industry, such as skilled labor shortages and ergonomic risks associated withwork-related musculoskeletal disorders. By integrating process design with AI-based algorithms into simulation tools, various construction process layout variants including robot-assisted scenarios can be simulated and evaluated based on user-specific key performance indicators (e.g., ergonomic score, layouting parameters) to identify optimized solutions. A data processing algorithm automates the process, eliminating the need for manual simulation variations and resulting in increased operational productivity. The AI-based system evaluates and optimizes process layouts by adjusting control parameters. A case study on a brick laying process serves as an exemplary use case, highlighting the necessity and impact of adopting process optimization. The findings emphasize the transformative potential of automated process optimization within simulation environments to rethink existing construction practices, enhance worker well-being, and boost operational productivity.}, language = {en} }