@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} }