@misc{14036,
  abstract     = {{This paper presents a robotic system developed to enhance automation in construction workflows through advanced AI
and computer vision technologies. The system integrates a robotic arm with a 3D point cloud camera and state-
of-the-art 2D pre-trained Deep Learning models, such as GroundingDINO and SegmentAnything, to detect and segment construction elements in 3D dynamic, unstructured environments. By processing point cloud data from the camera and aligning it with real-world coordinates, the system achieves precise object localization, enabling tasks such as
element handling and assembly. Designed to address challenges like clutter, occlusion, and variability in construction
sites, this system bridges the gap between controlled laboratory conditions and real-world applications. Experimental
evaluations highlight its potential to improve efficiency and adaptability in construction tasks.}},
  author       = {{Aykin, Yusuf and Sachs, Hans and Gerzen, Nikolai}},
  booktitle    = {{Proceedings of the 42th International Symposium on Automation and Robotics in Construction : Montreal, Canada, July 28-31, 2025}},
  editor       = {{Zhang, Jiansong and Chen, Qian and Lee, Gaang and Gonzalez, Vicente A. and Kamat, Vineet}},
  issn         = {{2413-5844}},
  keywords     = {{Computer Vision, Architecture, Building Construction, Robotics in Construction}},
  location     = {{Montreal, Canada}},
  publisher    = {{International Association for Automation and Robotics in Construction (IAARC)}},
  title        = {{{Enhancing Robotic Vision through Deep Learning Techniques: From Detection to Construction}}},
  doi          = {{10.22260/isarc2025/0026}},
  year         = {{2025}},
}

@inbook{13169,
  abstract     = {{KI.BAU is a project being developed and conducted at the Detmold School of Design, part of the University of Applied Sciences and Arts Ostwestfalen-Lippe. It focuses on researching the application of artificial intelligence (AI) in architectural design, modelling, production and management processes, particularly on the communication between users, processes and the building itself in various development and life-time phases. Hence the research aims to develop new tools and AI-supported process chains for the design, production and communication of architecture. This includes the training and implementing prototypical machine learning algorithms to autonomously evolve and optimize field-specific processes and workflows.
As mentioned above, a critical question KI.BAU explores is how we, as planners, builders and users, will communicate with architecture in the future, in its phases of creation and use but also beyond. This also involves, besides virtual interfaces, examining the physical interaction with a building, its behaviour, responsiveness and adaptation to certain conditions. 
The primary goal of the research at KI.BAU is to transform architecture into an intelligent, to some degree self-sustaining, self-reflective and maybe even evolving ‘ecological system’. This system should be comprehensively linked with its creators, users, devices, computers, its (biological) environment and networks. Consequently, a building must be viewed as an organism that communicates, interacts and adapts to other connected or related organisms and entities.
}},
  author       = {{Sachs, Hans}},
  booktitle    = {{Synthetic realities: New Frontiers in AI-driven Design, Fabrication and Materiality}},
  editor       = {{Kretzer, Manuel}},
  isbn         = {{978-3887781088}},
  keywords     = {{AI, Artificial Intelligence, Architecture, Build Environment, Building Construction, Ecology of Architecture}},
  pages        = {{14}},
  publisher    = {{AADR – Art Architecture Design Research}},
  title        = {{{KI.BAU Artificial Intelligence in Architecture}}},
  year         = {{2024}},
}