---
_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'
...