What question did this study set out to answer?

The main aim is to develop a system for detecting objects and monitoring changes in underground mines using 2D and 3D technologies.

March 1, 2026Applied SciencesOpen Access

Automated Object Detection and Change Quantification in Underground Mines Using LiDAR Point Clouds and 360° Image Processing

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Demonstrates a dual-pipeline system for hazard detection in underground mines, indicating improved safety outcomes.

The main aim is to develop a system for detecting objects and monitoring changes in underground mines using 2D and 3D technologies.
Developed a dual-pipeline framework combining 360° imaging and LiDAR scanning.
Utilized a Ricoh Theta Z1 camera for panoramic image capture.
Fine-tuned a YOLOv8n model for object detection in low light conditions.
Employed Ouster OS1-070-64 LiDAR sensor for 3D point cloud processing.
Implemented techniques like denoising, ICP alignment, and manual annotation for accurate measurements.
Fine-tuned YOLOv8n effectively detected personnel and vehicles under challenging conditions.
The 3D system localized objects and measured vehicle displacement using bounding-box centroids.
Demonstrated strong performance of both the 2D and 3D components.

Peralta et al. (2026) studied this question.

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