---
_id: '14036'
abstract:
- lang: eng
  text: "This paper presents a robotic system developed to enhance automation in construction
    workflows through advanced AI\r\nand computer vision technologies. The system
    integrates a robotic arm with a 3D point cloud camera and state-\r\nof-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\r\nelement handling and assembly. Designed to address challenges like clutter,
    occlusion, and variability in construction\r\nsites, this system bridges the gap
    between controlled laboratory conditions and real-world applications. Experimental\r\nevaluations
    highlight its potential to improve efficiency and adaptability in construction
    tasks."
author:
- first_name: Yusuf
  full_name: Aykin, Yusuf
  id: '84542'
  last_name: Aykin
- first_name: Hans
  full_name: Sachs, Hans
  id: '64589'
  last_name: Sachs
- first_name: Nikolai
  full_name: Gerzen, Nikolai
  id: '76704'
  last_name: Gerzen
citation:
  ama: 'Aykin Y, Sachs H, Gerzen N. <i>Enhancing Robotic Vision through Deep Learning
    Techniques: From Detection to Construction</i>. (Zhang J, Chen Q, Lee G, et al.,
    eds.). International Association for Automation and Robotics in Construction (IAARC);
    2025. doi:<a href="https://doi.org/10.22260/isarc2025/0026">10.22260/isarc2025/0026</a>'
  apa: 'Aykin, Y., Sachs, H., &#38; Gerzen, N. (2025). Enhancing Robotic Vision through
    Deep Learning Techniques: From Detection to Construction. In J. Zhang, Q. Chen,
    G. Lee, V. A. Gonzalez, V. Kamat, International Association for Automation and
    Robotics in Construction, &#38; nternational Symposium on Automation and Robotics
    in Construction (Eds.), <i>Proceedings of the 42th International Symposium on
    Automation and Robotics in Construction : Montreal, Canada, July 28-31, 2025</i>.
    International Association for Automation and Robotics in Construction (IAARC).
    <a href="https://doi.org/10.22260/isarc2025/0026">https://doi.org/10.22260/isarc2025/0026</a>'
  bjps: '<b>Aykin Y, Sachs H and Gerzen N</b> (2025) <i>Enhancing Robotic Vision through
    Deep Learning Techniques: From Detection to Construction</i>, Zhang J et al. (eds).
    International Association for Automation and Robotics in Construction (IAARC).'
  chicago: 'Aykin, Yusuf, Hans Sachs, and Nikolai Gerzen. <i>Enhancing Robotic Vision
    through Deep Learning Techniques: From Detection to Construction</i>. Edited by
    Jiansong Zhang, Qian Chen, Gaang Lee, Vicente A. Gonzalez, Vineet Kamat, International
    Association for Automation and Robotics in Construction, and nternational Symposium
    on Automation and Robotics in Construction. <i>Proceedings of the 42th International
    Symposium on Automation and Robotics in Construction : Montreal, Canada, July
    28-31, 2025</i>. International Association for Automation and Robotics in Construction
    (IAARC), 2025. <a href="https://doi.org/10.22260/isarc2025/0026">https://doi.org/10.22260/isarc2025/0026</a>.'
  chicago-de: 'Aykin, Yusuf, Hans Sachs und Nikolai Gerzen. 2025. <i>Enhancing Robotic
    Vision through Deep Learning Techniques: From Detection to Construction</i>. Hg.
    von Jiansong Zhang, Qian Chen, Gaang Lee, Vicente A. Gonzalez, Vineet Kamat, International
    Association for Automation and Robotics in Construction, und nternational Symposium
    on Automation and Robotics in Construction. <i>Proceedings of the 42th International
    Symposium on Automation and Robotics in Construction : Montreal, Canada, July
    28-31, 2025</i>. International Association for Automation and Robotics in Construction
    (IAARC). doi:<a href="https://doi.org/10.22260/isarc2025/0026">10.22260/isarc2025/0026</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Aykin, Yusuf</span> ; <span
    style="font-variant:small-caps;">Sachs, Hans</span> ; <span style="font-variant:small-caps;">Gerzen,
    Nikolai</span> ; <span style="font-variant:small-caps;">Zhang, J.</span> ; <span
    style="font-variant:small-caps;">Chen, Q.</span> ; <span style="font-variant:small-caps;">Lee,
    G.</span> ; <span style="font-variant:small-caps;">Gonzalez, V. A.</span> ; <span
    style="font-variant:small-caps;">Kamat, V.</span> ; <span style="font-variant:small-caps;">International
    Association for Automation and Robotics in Construction</span> ; <span style="font-variant:small-caps;">nternational
    Symposium on Automation and Robotics in Construction</span> (Hrsg.): <i>Enhancing
    Robotic Vision through Deep Learning Techniques: From Detection to Construction</i> :
    International Association for Automation and Robotics in Construction (IAARC),
    2025'
  havard: 'Y. Aykin, H. Sachs, N. Gerzen, Enhancing Robotic Vision through Deep Learning
    Techniques: From Detection to Construction, International Association for Automation
    and Robotics in Construction (IAARC), 2025.'
  ieee: 'Y. Aykin, H. Sachs, and N. Gerzen, <i>Enhancing Robotic Vision through Deep
    Learning Techniques: From Detection to Construction</i>. International Association
    for Automation and Robotics in Construction (IAARC), 2025. doi: <a href="https://doi.org/10.22260/isarc2025/0026">10.22260/isarc2025/0026</a>.'
  mla: 'Aykin, Yusuf, et al. “Enhancing Robotic Vision through Deep Learning Techniques:
    From Detection to Construction.” <i>Proceedings of the 42th International Symposium
    on Automation and Robotics in Construction : Montreal, Canada, July 28-31, 2025</i>,
    edited by Jiansong Zhang et al., International Association for Automation and
    Robotics in Construction (IAARC), 2025, <a href="https://doi.org/10.22260/isarc2025/0026">https://doi.org/10.22260/isarc2025/0026</a>.'
  short: 'Y. Aykin, H. Sachs, N. Gerzen, Enhancing Robotic Vision through Deep Learning
    Techniques: From Detection to Construction, International Association for Automation
    and Robotics in Construction (IAARC), 2025.'
  ufg: '<b>Aykin, Yusuf/Sachs, Hans/Gerzen, Nikolai</b>: Enhancing Robotic Vision
    through Deep Learning Techniques: From Detection to Construction, hg. von Zhang,
    Jiansong u. a., o. O. 2025.'
  van: 'Aykin Y, Sachs H, Gerzen N. Enhancing Robotic Vision through Deep Learning
    Techniques: From Detection to Construction. Zhang J, Chen Q, Lee G, Gonzalez VA,
    Kamat V, International Association for Automation and Robotics in Construction,
    et al., editors. Proceedings of the 42th International Symposium on Automation
    and Robotics in Construction : Montreal, Canada, July 28-31, 2025. International
    Association for Automation and Robotics in Construction (IAARC); 2025.'
conference:
  end_date: 2025-07-31
  location: Montreal, Canada
  name: '42th International Symposium on Automation and Robotics in Construction '
  start_date: 2025-07-28
corporate_editor:
- International Association for Automation and Robotics in Construction
- nternational Symposium on Automation and Robotics in Construction
date_created: 2026-09-17T14:27:18Z
date_updated: 2026-09-25T13:05:40Z
ddc:
- '600'
department:
- _id: DEP1055
- _id: DEP1624
doi: 10.22260/isarc2025/0026
editor:
- first_name: Jiansong
  full_name: Zhang, Jiansong
  last_name: Zhang
- first_name: Qian
  full_name: Chen, Qian
  last_name: Chen
- first_name: Gaang
  full_name: Lee, Gaang
  last_name: Lee
- first_name: Vicente A.
  full_name: Gonzalez, Vicente A.
  last_name: Gonzalez
- first_name: Vineet
  full_name: Kamat, Vineet
  last_name: Kamat
has_accepted_license: '1'
keyword:
- Computer Vision
- Architecture
- Building Construction
- Robotics in Construction
language:
- iso: eng
publication: 'Proceedings of the 42th International Symposium on Automation and Robotics
  in Construction : Montreal, Canada, July 28-31, 2025'
publication_identifier:
  eisbn:
  - 978-0-6458322-2-8
  eissn:
  - 2413-5844
publication_status: published
publisher: International Association for Automation and Robotics in Construction (IAARC)
quality_controlled: '1'
status: public
title: 'Enhancing Robotic Vision through Deep Learning Techniques: From Detection
  to Construction'
type: conference_editor_article
user_id: '83781'
year: '2025'
...
---
_id: '13169'
abstract:
- lang: eng
  text: "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.\r\nAs 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. \r\nThe 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.\r\n"
author:
- first_name: Hans
  full_name: Sachs, Hans
  id: '64589'
  last_name: Sachs
citation:
  ama: 'Sachs H. KI.BAU Artificial Intelligence in Architecture. In: Kretzer M, AADR
    – Art Architecture Design Research, eds. <i>Synthetic Realities: New Frontiers
    in AI-Driven Design, Fabrication and Materiality</i>. 1. AADR – Art Architecture
    Design Research; 2024:14.'
  apa: 'Sachs, H. (2024). KI.BAU Artificial Intelligence in Architecture. In M. Kretzer
    &#38; AADR – Art Architecture Design Research (Eds.), <i>Synthetic realities:
    New Frontiers in AI-driven Design, Fabrication and Materiality</i> (1., p. 14).
    AADR – Art Architecture Design Research.'
  bjps: '<b>Sachs H</b> (2024) KI.BAU Artificial Intelligence in Architecture. In
    Kretzer M and AADR – Art Architecture Design Research (eds), <i>Synthetic Realities:
    New Frontiers in AI-Driven Design, Fabrication and Materiality</i>, 1. Baunach:
    AADR – Art Architecture Design Research, p. 14.'
  chicago: 'Sachs, Hans. “KI.BAU Artificial Intelligence in Architecture.” In <i>Synthetic
    Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality</i>,
    edited by Manuel Kretzer and AADR – Art Architecture Design Research, 1., 14.
    Baunach: AADR – Art Architecture Design Research, 2024.'
  chicago-de: 'Sachs, Hans. 2024. KI.BAU Artificial Intelligence in Architecture.
    In: <i>Synthetic realities: New Frontiers in AI-driven Design, Fabrication and
    Materiality</i>, hg. von Manuel Kretzer und AADR – Art Architecture Design Research,
    14. 1. Baunach: AADR – Art Architecture Design Research.'
  din1505-2-1: '<span style="font-variant:small-caps;">Sachs, Hans</span>: KI.BAU
    Artificial Intelligence in Architecture. In: <span style="font-variant:small-caps;">Kretzer,
    M.</span> ; <span style="font-variant:small-caps;">AADR – Art Architecture Design
    Research</span> (Hrsg.): <i>Synthetic realities: New Frontiers in AI-driven Design,
    Fabrication and Materiality</i>. 1. Baunach : AADR – Art Architecture Design Research,
    2024, S. 14'
  havard: 'H. Sachs, KI.BAU Artificial Intelligence in Architecture, in: M. Kretzer,
    AADR – Art Architecture Design Research (Eds.), Synthetic Realities: New Frontiers
    in AI-Driven Design, Fabrication and Materiality, 1., AADR – Art Architecture
    Design Research, Baunach, 2024: p. 14.'
  ieee: 'H. Sachs, “KI.BAU Artificial Intelligence in Architecture,” in <i>Synthetic
    realities: New Frontiers in AI-driven Design, Fabrication and Materiality</i>,
    1., M. Kretzer and AADR – Art Architecture Design Research, Eds. Baunach: AADR
    – Art Architecture Design Research, 2024, p. 14.'
  mla: 'Sachs, Hans. “KI.BAU Artificial Intelligence in Architecture.” <i>Synthetic
    Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality</i>,
    edited by Manuel Kretzer and AADR – Art Architecture Design Research, 1., AADR
    – Art Architecture Design Research, 2024, p. 14.'
  short: 'H. Sachs, in: M. Kretzer, AADR – Art Architecture Design Research (Eds.),
    Synthetic Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality,
    1., AADR – Art Architecture Design Research, Baunach, 2024, p. 14.'
  ufg: '<b>Sachs, Hans</b>: KI.BAU Artificial Intelligence in Architecture, in: <i>Kretzer,
    Manuel, AADR – Art Architecture Design Research (Hgg.)</i>: Synthetic realities:
    New Frontiers in AI-driven Design, Fabrication and Materiality, <span style="baseline">1.</span>,
    Baunach 2024,  S. 14.'
  van: 'Sachs H. KI.BAU Artificial Intelligence in Architecture. In: Kretzer M, AADR
    – Art Architecture Design Research, editors. Synthetic realities: New Frontiers
    in AI-driven Design, Fabrication and Materiality. 1. Baunach: AADR – Art Architecture
    Design Research; 2024. p. 14.'
corporate_editor:
- AADR – Art Architecture Design Research
date_created: 2025-09-11T10:50:08Z
date_updated: 2025-10-16T20:54:48Z
department:
- _id: DEP1624
- _id: DEP1055
edition: '1.'
editor:
- first_name: Manuel
  full_name: Kretzer, Manuel
  last_name: Kretzer
jel:
- A31
keyword:
- AI
- Artificial Intelligence
- Architecture
- Build Environment
- Building Construction
- Ecology of Architecture
language:
- iso: eng
page: '14'
place: Baunach
popular_science: '1'
publication: 'Synthetic realities: New Frontiers in AI-driven Design, Fabrication
  and Materiality'
publication_identifier:
  isbn:
  - 978-3887781088
publication_status: published
publisher: AADR – Art Architecture Design Research
related_material:
  link:
  - relation: new_edition
    url: https://aadr.info/product/synthetic-realities/
status: public
title: KI.BAU Artificial Intelligence in Architecture
type: book_chapter
user_id: '64589'
year: '2024'
...