---
_id: '14036'
abstract:
- lang: eng
text: "This paper presents a robotic system developed to enhance\r\nautomation in
construction workflows through advanced AI\r\nand computer vision technologies.
The system integrates\r\na robotic arm with a 3D point cloud camera and state-\r\nof-the-art
2D pre-trained Deep Learning models, such as\r\nGroundingDINO and SegmentAnything,
to detect and seg-\r\nment construction elements in 3D dynamic, unstructured\r\nenvironments.
By processing point cloud data from the cam-\r\nera and aligning it with real-world
coordinates, the system\r\nachieves precise object localization, enabling tasks
such as\r\nelement handling and assembly. Designed to address chal-\r\nlenges
like clutter, occlusion, and variability in construction\r\nsites, this system
bridges the gap between controlled labora-\r\ntory conditions and real-world applications.
Experimental\r\nevaluations highlight its potential to improve efficiency and\r\nadaptability
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. Enhancing Robotic Vision through Deep Learning
Techniques: From Detection to Construction. (Sachs H, ed.). International
Association for Automation and Robotics in Construction (IAARC); 2025. doi:10.22260/isarc2025/0026'
apa: 'Aykin, Y., Sachs, H., & Gerzen, N. (2025). Enhancing Robotic Vision through
Deep Learning Techniques: From Detection to Construction. In H. Sachs (Ed.), Proceedings
of the International Symposium on Automation and Robotics in Construction (IAARC).
International Association for Automation and Robotics in Construction (IAARC).
https://doi.org/10.22260/isarc2025/0026'
bjps: 'Aykin Y, Sachs H and Gerzen N (2025) Enhancing Robotic Vision through
Deep Learning Techniques: From Detection to Construction, Sachs H (ed.). International
Association for Automation and Robotics in Construction (IAARC).'
chicago: 'Aykin, Yusuf, Hans Sachs, and Nikolai Gerzen. Enhancing Robotic Vision
through Deep Learning Techniques: From Detection to Construction. Edited by
Hans Sachs. Proceedings of the International Symposium on Automation and Robotics
in Construction (IAARC). International Association for Automation and Robotics
in Construction (IAARC), 2025. https://doi.org/10.22260/isarc2025/0026.'
chicago-de: 'Aykin, Yusuf, Hans Sachs und Nikolai Gerzen. 2025. Enhancing Robotic
Vision through Deep Learning Techniques: From Detection to Construction. Hg.
von Hans Sachs. Proceedings of the International Symposium on Automation and
Robotics in Construction (IAARC). International Association for Automation
and Robotics in Construction (IAARC). doi:10.22260/isarc2025/0026,
.'
din1505-2-1: 'Aykin, Yusuf ; Sachs, Hans ; Gerzen,
Nikolai ; Sachs, H. (Hrsg.):
Enhancing Robotic Vision through Deep Learning Techniques: From Detection to
Construction : 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, Enhancing Robotic Vision through Deep
Learning Techniques: From Detection to Construction. International Association
for Automation and Robotics in Construction (IAARC), 2025. doi: 10.22260/isarc2025/0026.'
mla: 'Aykin, Yusuf, et al. “Enhancing Robotic Vision through Deep Learning Techniques:
From Detection to Construction.” Proceedings of the International Symposium
on Automation and Robotics in Construction (IAARC), edited by Hans Sachs,
International Association for Automation and Robotics in Construction (IAARC),
2025, https://doi.org/10.22260/isarc2025/0026.'
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: 'Aykin, Yusuf/Sachs, Hans/Gerzen, Nikolai: Enhancing Robotic Vision
through Deep Learning Techniques: From Detection to Construction, hg. von Sachs,
Hans, o. O. 2025.'
van: 'Aykin Y, Sachs H, Gerzen N. Enhancing Robotic Vision through Deep Learning
Techniques: From Detection to Construction. Sachs H, editor. Proceedings of the
International Symposium on Automation and Robotics in Construction (IAARC). International
Association for Automation and Robotics in Construction (IAARC); 2025.'
date_created: 2026-09-17T14:27:18Z
date_updated: 2026-09-17T14:43:42Z
ddc:
- '600'
department:
- _id: DEP1055
doi: 10.22260/isarc2025/0026
editor:
- first_name: Hans
full_name: Sachs, Hans
id: '64589'
last_name: Sachs
file:
- access_level: open_access
content_type: application/pdf
creator: fpq-3n9
date_created: 2026-09-17T14:43:28Z
date_updated: 2026-09-17T14:43:28Z
file_id: '14039'
file_name: ISARC_Robotic_Vision_Yusuf_Aykin.pdf
file_size: 4708066
relation: main_file
success: 1
file_date_updated: 2026-09-17T14:43:28Z
has_accepted_license: '1'
keyword:
- Computer Vision
- Architecture
- Building Construction
- Robotics in Construction
language:
- iso: eng
oa: '1'
publication: Proceedings of the International Symposium on Automation and Robotics
in Construction (IAARC)
publication_identifier:
issn:
- 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: '64589'
year: '2025'
...