@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} } @article{LinnerdeSotoElMahdyetal., author = {Linner, Thomas and de Soto, Borja Garc{\´i}a and El-Mahdy, Deena and Gonzalez, Vicente A.}, title = {Topical collection: robotic solutions for digitally enabled production processes in construction}, series = {Construction Robotics}, volume = {10}, journal = {Construction Robotics}, publisher = {Springer}, issn = {2509-811X}, doi = {10.1007/s41693-025-00174-w}, pages = {1}, abstract = {Across the global construction sector, a new generation of robotic systems is rapidly entering the market. Solutions for on-site drilling, spraying, masonry, logistics, and finishing are now being piloted at an unprecedented pace. Their deployment in emerging construction robotics hubs in Singapore, Hong Kong, Canada, Dubai, Abu Dhabi, Egypt, Denmark, Switzerland, and Germany demonstrates both the momentum of this technological shift and the considerable challenges that remain. In real-world testing environments, the integration of these robots into digital construction pipelines—particularly BIM-to-robot workflows, semantic task modeling, and robust digital twins—continues to be a bottleneck. These challenges position digitally enabled fabrication and robotics as a priority topic within academia, motivating research on methods, techniques, algorithms, and workflows that can accelerate adoption in construction. This Topical Collection brings together research spanning the emerging landscape of digitally enabled construction robotics. The contributions advance robotic fabrication, from flexible timber processes to innovative formwork, reinforcement, and earth-based additive methods, alongside computer vision, BIM integration, and sensing approaches that improve monitoring and quality assurance. The collection also includes mobile and aerial systems for inspection and mapping to support system autonomy in construction. Together, these works show how integrated perception, planning, and sociotechnical understanding of human-robot collaboration are becoming essential for reliable robotic performance in construction. While current construction robots still focus on simple, structured tasks, the advances in this topical collection point toward a more capable generation. Contributions outline principles for robot-compatible buildings through new fabrication logics and BIM-linked task data, while work on perception, BIM integration, and data fusion reduces interoperability gaps. Research on sensing and adaptive processes supports more consistent workflows, and mobile and aerial robotics provide insights for deployment and site logistics. Collectively, these developments show how digitally enabled production processes can help to overcome key systemic barriers and enable future, scalable construction robotics.}, language = {en} }