Aerial Robotics for Mining

Aerial Robotics for Mining

In this project we aim to develop UAV based monitoring and data acquisition solutions that enable efficient and timely decision-making for mine-to-mill process optimisation. This involves monitoring drilling and blasting practices for real-time rock fragmentation analysis, monitoring and assessing ore dilution in post-blast muck piles and inspection and monitoring of surface excavations and earthworks. The combination of UAV and sensing technologies in this project will help to enable continuous mining process control and optimisation.

 

Related Publications

Point-cloud-based aerial fragmentation analysis for application in the minerals industry
T. Bamford, K. Esmaeili, and A. P. Schoellig
Technical Report, arXiv, 2017.
[View BibTeX] [View Abstract] [Download PDF] [More Information]
This work investigates the application of Unmanned Aerial Vehicle (UAV) technology for measurement of rock fragmentation without placement of scale objects in the scene to determine image scale. Commonly practiced image-based rock fragmentation analysis requires a technician to walk to a rock pile, place a scale object of known size in the area of interest, and capture individual 2D images. Our previous work has used UAV technology for the first time to acquire real-time rock fragmentation data and has shown comparable quality of results; however, it still required the (potentially dangerous) placement of scale objects, and continued to make the assumption that the rock pile surface is planar and that the scale objects lie on the surface plane. This work improves our UAV-based approach to enable rock fragmentation measurement without placement of scale objects and without the assumption of planarity. This is achieved by first generating a point cloud of the rock pile from 2D images, taking into account intrinsic and extrinsic camera parameters, and then taking 2D images for fragmentation analysis. This work represents an important step towards automating post-blast rock fragmentation analysis. In experiments, a rock pile with known size distribution was photographed by the UAV with and without using scale objects. For fragmentation analysis without scale objects, a point cloud of the rock pile was generated and used to compute image scale. Comparison of the rock size distributions show that this point-cloud-based method enables producing measurements with better or comparable accuracy (within 10% of the ground truth) to the manual method with scale objects.

@TECHREPORT{bamford-iros17,
title = {Point-cloud-based aerial fragmentation analysis for application in the minerals industry},
institution = {arXiv},
author = {Thomas Bamford and Kamran Esmaeili and Angela P. Schoellig},
year = {2017},
urllink = {https://arxiv.org/abs/1703.01945},
abstract = {This work investigates the application of Unmanned Aerial Vehicle (UAV) technology for measurement of rock fragmentation without placement of scale objects in the scene to determine image scale. Commonly practiced image-based rock fragmentation analysis requires a technician to walk to a rock pile, place a scale object of known size in the area of interest, and capture individual 2D images. Our previous work has used UAV technology for the first time to acquire real-time rock fragmentation data and has shown comparable quality of results; however, it still required the (potentially dangerous) placement of scale objects, and continued to make the assumption that the rock pile surface is planar and that the scale objects lie on the surface plane. This work improves our UAV-based approach to enable rock fragmentation measurement without placement of scale objects and without the assumption of planarity. This is achieved by first generating a point cloud of the rock pile from 2D images, taking into account intrinsic and extrinsic camera parameters, and then taking 2D images for fragmentation analysis. This work represents an important step towards automating post-blast rock fragmentation analysis. In experiments, a rock pile with known size distribution was photographed by the UAV with and without using scale objects. For fragmentation analysis without scale objects, a point cloud of the rock pile was generated and used to compute image scale. Comparison of the rock size distributions show that this point-cloud-based method enables producing measurements with better or comparable accuracy (within 10% of the ground truth) to the manual method with scale objects.},
}

[DOI] A real-time analysis of post-blast rock fragmentation using UAV technology
T. Bamford, K. Esmaeili, and A. P. Schoellig
International Journal of Mining, Reclamation and Environment, vol. 31, iss. 6, pp. 439-456, 2017.
[View BibTeX] [View Abstract] [Download PDF] [View Video]

The current practice of collecting rock fragmentation data for image analysis is highly manual and provides data with low temporal and spatial resolution. Using Unmanned Aerial Vehicles (UAVs) for collecting images of rock fragments improves the quality of the image data and automates the data collection process. This work presents the results of laboratory-scale using a UAV. The goal is to highlight the benefits of aerial fragmentation analysis in terms of both prediction accuracy and time effort. The pile was manually photographed and the results of the manual method were compared to the UAV method.

@article{bamford-ijmre17,
title = {A Real-Time Analysis of Post-Blast Rock Fragmentation Using {UAV} Technology},
author = {Bamford, Thomas and Esmaeili, Kamran and Schoellig, Angela P.},
journal = {{International Journal of Mining, Reclamation and Environment}},
year = {2017},
volume = {31},
number = {6},
doi = {10.1080/17480930.2017.1339170},
pages = {439--456},
publisher = {Taylor & Francis},
urlvideo = {https://youtu.be/q0syk6J_JHY},
abstract = {The current practice of collecting rock fragmentation data for image analysis is highly manual and provides data with low temporal and spatial resolution. Using Unmanned Aerial Vehicles (UAVs) for collecting images of rock fragments improves the quality of the image data and automates the data collection process. This work presents the results of laboratory-scale using a UAV. The goal is to highlight the benefits of aerial fragmentation analysis in terms of both prediction accuracy and time effort. The pile was manually photographed and the results of the manual method were compared to the UAV method.},
}

Aerial rock fragmentation analysis in low-light condition using UAV technology
T. Bamford, K. Esmaeili, and A. P. Schoellig
in Proc. of Application of Computers and Operations Research in the Mining Industry (APCOM), 2017, p. 4-1–4-8.
[View BibTeX] [View Abstract] [Download PDF] [Download Slides]

In recent years, Unmanned Aerial Vehicle (UAV) technology has been introduced into the mining industry to conduct terrain surveying. This work investigates the application of UAVs with artificial lighting for measurement of rock fragmentation under poor lighting conditions, representing night shifts in surface mines or working conditions in underground mines. The study relies on indoor and outdoor experiments for rock fragmentation analysis using a quadrotor UAV. Comparison of the rock size distributions in both cases show that adequate artificial lighting enables similar accuracy to ideal lighting conditions.

@INPROCEEDINGS{bamford-apcom17,
author={Thomas Bamford and Kamran Esmaeili and Angela P. Schoellig},
title={Aerial Rock Fragmentation Analysis in Low-Light Condition Using {UAV} Technology},
booktitle={{Proc. of Application of Computers and Operations Research in the Mining Industry (APCOM)}},
year={2017},
pages = {4-1--4-8},
urlslides={../../wp-content/papercite-data/slides/bamford-apcom17-slides.pdf},
abstract={In recent years, Unmanned Aerial Vehicle (UAV) technology has been introduced into the mining industry to conduct terrain surveying. This work investigates the application of UAVs with artificial lighting for measurement of rock fragmentation under poor lighting conditions, representing night shifts in surface mines or working conditions in underground mines. The study relies on indoor and outdoor experiments for rock fragmentation analysis using a quadrotor UAV. Comparison of the rock size distributions in both cases show that adequate artificial lighting enables similar accuracy to ideal lighting conditions.},
}

Rock fragmentation analysis using UAV technology
T. Bamford, K. Esmaeili, and A. P. Schoellig
Professional Magazine Article, Ontario Professional Surveyor (OPS) Magazine, Assn. of Ontario Land Surveyors, 2016.
[View BibTeX] [Download PDF] [More Information]

@MISC{bamford-ops16,
author = {Thomas Bamford and Kamran Esmaeili and Angela P. Schoellig},
title = {Rock fragmentation analysis using {UAV} technology},
year = {2016},
volume = {59},
number = {4},
pages = {14-16},
howpublished = {Professional Magazine Article, Ontario Professional Surveyor (OPS) Magazine, Assn. of Ontario Land Surveyors},
urllink = {http://publications.aols.org/OPS-Magazine/2016Fall/},
}

A real-time analysis of rock fragmentation using UAV technology
T. Bamford, K. Esmaeili, and A. P. Schoellig
in Proc. of the International Conference on Computer Applications in the Minerals Industries (CAMI), 2016.
[View BibTeX] [View Abstract] [Download PDF] [View Video] [Download Slides] [More Information]

Accurate measurement of blast-induced rock fragmentation is of great importance for many mining operations. The post-blast rock size distribution can significantly influence the efficiency of all the downstream mining and comminution processes. Image analysis methods are one of the most common methods used to measure rock fragment size distribution in mines regardless of criticism for lack of accuracy to measure fine particles and other perceived deficiencies. The current practice of collecting rock fragmentation data for image analysis is highly manual and provides data with low temporal and spatial resolution. Using Unmanned Aerial Vehicles (UAVs) for collecting images of rock fragments can not only improve the quality of the image data but also automate the data collection process. Ultimately, real-time acquisition of high temporal- and spatial-resolution data based on UAV technology will provide a broad range of opportunities for both improving blast design without interrupting the production process and reducing the cost of the human operator.

@INPROCEEDINGS{bamford-cami16,
author = {Thomas Bamford and Kamran Esmaeili and Angela P. Schoellig},
title = {A real-time analysis of rock fragmentation using {UAV} technology},
booktitle = {{Proc. of the International Conference on Computer Applications in the Minerals Industries (CAMI)}},
year = {2016},
urllink = {http://arxiv.org/abs/1607.04243},
urlvideo = {https://youtu.be/q0syk6J_JHY},
urlslides={../../wp-content/papercite-data/slides/bamford-cami16-slides.pdf},
abstract = {Accurate measurement of blast-induced rock fragmentation is of great importance for many mining operations. The post-blast rock size distribution can significantly influence the efficiency of all the downstream mining and comminution processes. Image analysis methods are one of the most common methods used to measure rock fragment size distribution in mines regardless of criticism for lack of accuracy to measure fine particles and other perceived deficiencies. The current practice of collecting rock fragmentation data for image analysis is highly manual and provides data with low temporal and spatial resolution. Using Unmanned Aerial Vehicles (UAVs) for collecting images of rock fragments can not only improve the quality of the image data but also automate the data collection process. Ultimately, real-time acquisition of high temporal- and spatial-resolution data based on UAV technology will provide a broad range of opportunities for both improving blast design without interrupting the production process and reducing the cost of the human operator.},
}

University of Toronto Institute for Aerospace Studies