Abstract
With the rapid development of smart manufacturing and automation technology, many factories have adopted autonomous inspection systems to enhance operational efficiency and safety. In particular, steel mills operate in extreme environments characterized by structural height variations, high temperatures, and heavy steel dust, making traditional manual inspections hazardous, labor-intensive, and inefficient. These challenges highlight the need for high-precision and automated inspection technologies. LiDAR-SLAM (Simultaneous Localization and Mapping) has emerged as a key solution for industrial mapping and autonomous inspection. By constructing high-precision environmental models, LiDAR-SLAM enables inspection systems to perform positioning in complex, dynamic industrial environments with enhanced accuracy and stability. The robust localization framework provides a reliable foundation for autonomous inspection and precise positioning in steel product lines. This paper explores the application of LiDAR-SLAM technology for heavy industry inspections and its broader applications in industrial environments. The study demonstrates its potential to enhance inspection accuracy, improve workplace safety, and streamline operational management, contributing to the wider adoption of autonomous inspection systems in smart manufacturing.
| Original language | English |
|---|---|
| Title of host publication | ICCE-Taiwan 2025 - 12th IEEE International Conference on Consumer Electronics - Taiwan |
| Subtitle of host publication | Generative AI in Innovative Consumer Technology, Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 395-396 |
| Number of pages | 2 |
| ISBN (Electronic) | 9798331587413 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 12th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2025 - Kaohsiung, Taiwan Duration: 2025 Jul 16 → 2025 Jul 18 |
Publication series
| Name | ICCE-Taiwan 2025 - 12th IEEE International Conference on Consumer Electronics - Taiwan: Generative AI in Innovative Consumer Technology, Proceedings |
|---|
Conference
| Conference | 12th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2025 |
|---|---|
| Country/Territory | Taiwan |
| City | Kaohsiung |
| Period | 25-07-16 → 25-07-18 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Electrical and Electronic Engineering
- Media Technology
- Modelling and Simulation
- Instrumentation
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