Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Leveling Equipment01:18

Leveling Equipment

As leveling involves measuring vertical distances relative to a horizontal line of sight, it requires a graduated rod, called a level rod, for vertical measurements and an instrument called a level for a horizontal sight line. A level includes a high-powered telescope with a mechanism for leveling to ensure the line of sight is horizontal when the bubble in the spirit level is centered. Leveling rods, made of wood, metal, or fiberglass, are graduated in feet or meters and commonly used in two-...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Computer Vision for Autonomous Drill Jumbos: Detecting Non-Drillable Areas of a Mine Face.

Sensors (Basel, Switzerland)·2026
Same author

LoRa-Based Data Mule Technology for Fuel Station Monitoring in Underground Mining.

Sensors (Basel, Switzerland)·2026
Same author

LoRa Propagation and Coverage Measurements in Underground Potash Salt Room-and-Pillar Mines.

Sensors (Basel, Switzerland)·2025
See all related articles

Related Experiment Video

Updated: Jun 23, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.2K

Stereo Vision-Based Underground Muck Pile Detection for Autonomous LHD Bucket Loading.

Emilia Hennen1, Adam Pekarski1, Violetta Storoschewich1

  • 1Institute for Advanced Mining Technologies (AMT), RWTH Aachen University, 52062 Aachen, Germany.

Sensors (Basel, Switzerland)
|September 13, 2025
PubMed
Summary

This study introduces a new stereo camera system for autonomous mining. It accurately detects and maps muck piles, enabling load-haul-dump machines to load material safely and efficiently without human intervention.

Keywords:
LHDautomationenvironmental perceptionstereo visionunderground mining

More Related Videos

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.4K
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.6K

Related Experiment Videos

Last Updated: Jun 23, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.2K
Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.4K
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.6K

Area of Science:

  • Robotics and Automation
  • Geospatial Data Processing
  • Mining Engineering

Background:

  • Advancing automation in underground mining is crucial for safety and efficiency.
  • Current autonomous loading systems for load-haul-dump (LHD) machines face limitations in varying mine layouts and lack depth perception from 2D imaging.
  • Accurate detection and characterization of muck piles are essential for autonomous material loading.

Purpose of the Study:

  • To develop and validate a novel system for muck pile detection and characterization using stereo vision on LHD machines.
  • To enable autonomous material loading by providing accurate spatial and geometric information of muck piles.
  • To enhance the safety and efficiency of underground mining operations through advanced automation.

Main Methods:

  • Utilized a stereo camera mounted on an LHD to capture 3D data of the mining environment.
  • Applied a topological algorithm to detect and segment muck piles from the gathered 3D data.
  • Integrated the muck pile detection system with LHD control for autonomous loading operations.

Main Results:

  • The developed system successfully detects and segments muck piles in real-time, even while the LHD is in motion.
  • The system accurately determines the spatial configuration and geometry of muck piles.
  • Demonstrated reliable autonomous material loading by LHD machines in two underground mine settings.

Conclusions:

  • The novel stereo vision and topological algorithm approach enables robust muck pile detection for autonomous LHD operation.
  • This technology significantly advances the potential for fully autonomous material loading in underground mines.
  • The system contributes to increased safety and efficiency in mining automation.