Yolo Deep Model for Pallet Recognition Contribution into Industrial Area
Recent object detection developments have been largely influenced by advances in the field of deep learning. In this context, we have developed a pallet detection model integrated into a forklift robot in order to optimize the picking process in storage and logistics environments in industrial settings. The project based on the architecture of the YOLO (You Only Look Once) model to improve pallet recognition and estimation of position and distance allowing robots to autonomously locate and pick pallets. This model stands out for its ability to provide fast and accurate object detection in high-resolution images, making them particularly suitable for real-time applications such as robotics and logistics.
Authors
- Chokri Souani (ORCID: https://orcid.org/0000-0002-8987-3582)
- Anis Ammar (ORCID: https://orcid.org/0000-0002-6588-8739)
- Rim Ghozzi (ORCID: https://orcid.org/0000-0002-0140-4731)
- Souhir Sghaier (ORCID: https://orcid.org/0000-0003-3523-1426)
- Gassab Aziz
Institutions
- University of Monastir (TN)
- Taif University (SA)
- University of Sousse (TN)
Publication Details
- Published
- 2025-04-13
- DOI
- https://doi.org/10.1109/iccit63348.2025.10989317
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00