@article{medinac-mme20,
title = {Haul road monitoring in open pit mines using unmanned aerial vehicles: A case study at {Bald Mountain} mine site},
author = {Filip Medinac and Thomas Bamford and Matthew Hart and Michal Kowalczyk and Kamran Esmaeili},
journal = {{Mining, Metallurgy \& Exploration}},
year = {2020},
volume = {37},
pages = {1877--1883},
doi = {10.1007/s42461-020-00291-w},
urllink = {https://rdcu.be/cbOuJ},
abstract = {Improved haul road conditions can positively impact mine operations resulting in increased safety, productivity gains, increased tire life, and lower maintenance costs. For these reasons, a monitoring program is required to ensure the operational efficiency of the haul roads. Currently, at Bald Mountain mine, monthly site severity studies, ad hoc inspections by frontline supervisors, or operator feedback reporting is used to assess road conditions. These methods are subjective and provide low temporal resolution data. This case study presents novel unmanned aerial vehicle (UAV) technologies, applied on a critical section of haul road at Bald Mountain, to showcase the potential for monitoring haul roads. The results show that orthophotos and digital elevation models can be used to assess the road smoothness condition and to check the road design compliance. Moreover, the aerial mapping allows detection of surface water, rock spillage, and potholes on the road that can be quickly repaired/removed by the dedicated road maintenance team.},
}

@INPROCEEDINGS{medinac-dfne18,
author = {Filip Medinac and Thomas Bamford and Kamran Esmaeili and Angela P. Schoellig},
title = {Pre- and post-blast rock block size analysis using {UAV-Lidar} based data and discrete fracture network},
booktitle = {{Proc. of the 2nd International Discrete Fracture Network Engineering (DFNE)}},
year = {2018},
abstact = {Drilling and blasting is one of the key processes in open pit mining, required to reduce in-situ rock block size to rock fragments that can be handled by mine equipment. It is a significant cost driver of any mining operation which can influence the downstream mining processes. In-situ rock block size influences the muck pile size distribution after blast, and the amount of drilling and explosive required to achieve a desired distribution. Thus, continuous measurement of pre- and post-blast rock block size distribution is essential for the optimization of the rock fragmentation process. This paper presents the results of a case study in an open pit mine where an Unmanned Aerial Vehicle (UAV) was used for mapping of the pit walls before blast. Pit wall mapping and aerial data was used as input to generate a 3D Discrete Fracture Network (DFN) model of the rock mass and to estimate the in-situ block size distribution. Data collected by the UAV was also used to estimate the post-blast rock fragment size distribution. The knowledge of in-situ and blasted rock size distributions can be related to assess blast performance. This knowledge will provide feedback to production engineers to adjust the blast design.},
}

@inproceedings{bamford-fragblast12,
author = {Thomas Bamford and Kamran Esmaeili and Angela P. Schoellig},
title = {Evaluation of {UAV} system accuracy for automated fragmentation measurement},
booktitle = {{Proc. of the 12th International Symposium on Rock Fragmentation by Blasting (FRAGBLAST)}},
year = {2018},
pages = {715--730},
abstract = {The current practice of collecting rock fragmentation data is highly manual and provides data with low temporal and spatial resolution. Unmanned Aerial Vehicle (UAV) technology can increase both temporal and spatial data resolution without exposing technicians to hazardous conditions. Our previous works using UAV technology to acquire real-time rock fragmentation data has shown comparable quality results to sieving in a lab environment. However, when applied to a mining environment, it is essential to quantify the accuracy of scale estimation and rock size distribution by considering various sources of uncertainties such as the UAV GPS, which provides noisy measurements. In the current paper, we investigate the accuracy of application of UAVs to collect photographic data for fragmentation analysis. This is done by evaluating the accuracy of the 3D model generated using the UAV system, estimated image scale, and the measured rock size distribution. This paper also investigates the impact of flight altitude on the measured rock size distribution.},
}

@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.},
}

@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.},
}

@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.},
}

@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.},
}

@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/},
}