Article
Drone-Assisted Confined Space Inspection and Stockpile
Volume Estimation
Ahmad Alsayed
1,2,
* , Akilu Yunusa-Kaltungo
1
, Mark K. Quinn
1
, Farshad Arvin
3
and Mostafa R. A. Nabawy
1,4
Citation: Alsayed, A.;
Yunusa-Kaltungo, A.; Quinn, M.K.;
Arvin, F.; Nabawy, M.R.A.
Drone-Assisted Confined Space
Inspection and Stockpile Volume
Estimation. Remote Sens. 2021, 13,
3356. https://doi.org/10.3390/
rs13173356
Academic Editors: George
Nikolakopoulos, Pablo
Rodríguez-Gonzálvez and Diego
González-Aguilera
Received: 10 June 2021
Accepted: 18 August 2021
Published: 24 August 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1
Department of Mechanical, Aerospace and Civil Engineering, The University of Manchester,
Manchester M1 3BB, UK; akilu.kaltungo@manchester.ac.uk (A.Y.-K.);
mark.quinn@manchester.ac.uk (M.K.Q.); mostafa.ahmednabawy@manchester.ac.uk (M.R.A.N.)
2
Department of Mechanical Engineering, Umm Al-Qura University, Makkah 5555, Saudi Arabia
3
Department of Electrical and Electronic Engineering, The University of Manchester, Manchester M1 3BB, UK;
farshad.arvin@manchester.ac.uk
4
Aerospace Engineering Department, Faculty of Engineering, Cairo University, Giza 12613, Egypt
* Correspondence: ahmad.alsayed@manchester.ac.uk
Abstract:
The accuracy of stockpile estimations is of immense criticality to process optimisation
and overall financial decision making within manufacturing operations. Despite well-established
correlations between inventory management and profitability, safe deployment of stockpile measure-
ment and inspection activities remain challenging and labour-intensive. This is perhaps owing to a
combination of size, shape irregularity as well as the health hazards of cement manufacturing raw
materials and products. Through a combination of simulations and real-life assessment within a fully
integrated cement plant, this study explores the potential of drones to safely enhance the accuracy of
stockpile volume estimations. Different types of LiDAR sensors in combination with different flight
trajectory options were fully assessed through simulation whilst mapping representative stockpiles
placed in both open and fully confined areas. During the real-life assessment, a drone was equipped
with GPS for localisation, in addition to a 1D LiDAR and a barometer for stockpile height estimation.
The usefulness of the proposed approach was established based on mapping of a pile with unknown
volume in an open area, as well as a pile with known volume within a semi-confined area. Visual
inspection of the generated stockpile surface showed strong correlations with the actual pile within
the open area, and the volume of the pile in the semi-confined area was accurately measured. Finally,
a comparative analysis of cost and complexity of the proposed solution to several existing initiatives
revealed its proficiency as a low-cost robotic system within confined spaces whereby visibility, air
quality, humidity, and high temperature are unfavourable.
Keywords:
drone; stockpile modelling; volume estimation; cement industry; confined space;
process safety
1. Introduction
Manufacturing operations such as cement processes are heavily dependent on stock-
piles of different materials that serve as inputs and outputs to and from various stages of
production. However, due to the potential adverse effects of atmospheric conditions on
cement manufacturing raw materials, most stockpiles are stored within confined spaces
such as silos, sheds, and hoppers. Whilst there are existing approaches for automated
storage mapping such as using laser scanners [
1
], there is still an essential need for low-cost,
low-intervention, and highly versatile solutions for such high-hazard industries. Un-
manned aerial vehicles (UAVs), commonly known as drones, are developed with different
configurations and have been deployed to tackle challenges in wide range of applica-
tions [
2
–
8
]. Recent years have witnessed increased use of drones within a variety of civil
applications such as monitoring of difficult-to-access infrastructures, spraying fields and
Remote Sens. 2021, 13, 3356. https://doi.org/10.3390/rs13173356 https://www.mdpi.com/journal/remotesensing
