Autonomous equipment

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Ore bodies are getting harder to access due to the increasing depth and harsh underground environments, such as high humidity and temperatures. These settings can be unsafe for the underground workforce, so reducing or eliminating the number of people working underground is becoming a common goal in the mining industry. Along with increasing safety, autonomous vehicles offer an opportunity to increase productivity and lower operating costs. These benefits can be achieved through both the elimination or reduction of the number of operators required, and lowering maintenance costs through more consistent operation following implementation of new technology. It also provides the benefit of lowering time lost while moving between the surface and the active work face, as the operator does not have to travel to the face anymore and can operate the machine from an office above ground [1]. . This article will focus on the underground applications of autonomy, however autonomous vehicles also have the potential to be implemented in open pit environments as well.

Difference Between Tele-remote and Fully Automated

It is important to distinguish the difference between tele-remote and fully autonomous vehicles. A tele-remote operation has an operator who to remotely controls the machines from any location in or outside the mine. Alternatively, a fully autonomous vehicle is able to execute tasks without real time human input, and can drive or tram between destinations, by autonomously taking into account the surroundings [2]. Currently both types of systems are utilized within the mining industry, independently as well as simultaneously. This article will focus on underground applications of tele-remote and fully automated vehicles, such as Load-Haul-Dump (LHD), trucks, drill rigs and trains.


The implementation of any autonomous system poses some challenges. First, the vehicles must have additional software and parts (like sensors, radar or lasers) to make communication possible between the operator and the vehicle, as well as to navigate through predetermined routes. In underground environments, GPS systems cannot be used so alternatives are required. One alternative is a Wireless Sensor Network which can create a communication mechanism between objects to improve overall control, visibility and cumulative utilization through real time location awareness [3]. This is also critical because the system must stay up-to-date with the dynamic mining environment. The harsh conditions of underground mines is one of the main drivers for automation, but also results in challenges as all additional systems must work under these rough conditions. Finally, in the transition period of human operated vehicles to autonomy, mixing humans with autonomous machines is unavoidable and therefore is a critical stage, as human safety cannot be compromised. Currently, this is overcome by separating autonomous or tele-remote areas from humans, but this results in a variety of limitations. The development of automation so far has not proved to be a driver for changing mining methods.

Load Haul Dump Vehicles

Load Haul Dump (LHD) vehicles are often exploited to do a combination of remote controlled and automated tasks. As an example, loading can be done by an operator who is located outside the mine, controlling the bucket remotely. After this is done, the operator is able to shift the LHD to an automated driving task, which will direct the LHD to the designated location, e.g. an ore chute or crusher. This has advantages when the LHD must access an unstable portion of the mine, such as draw points so that the safety of the worker is guaranteed. Another advantage is that one operator can control several LHDs at the same time, reducing total operating costs. Conversely, it can also reduce the productivity of a single LHD if there are visibility or operator feedback issues. There is also the possibility that the driving tasks cannot be executed fully autonomously, and the remote operator is limited to the control of one vehicle. A good example for where (semi)-automated LHDs are used is the Kiruna Mine located in Sweden. ¬

To ensure a feasible case for automated LHDs compared to man-operated vehicles, there are a few requirements that must be met according to Larsson [4], which are changing as the mining industry is growing towards a view where all humans must be removed from the mining operation. Currently, these requirements are minimal infrastructure and maintenance effort, while also guaranteeing extremely high safety and reliability. The control algorithms should also be designed to operate the vehicle in such a way that the maintenance of the vehicle can be kept to a minimum. [4]

Besides the advantages presented earlier in the article, there are other ways to improve productivity by utilizing automation for LHDs. Since LHDs will run without an operator, the overall utilization per LHD would be much higher as the only downtime results from maintenance, repair or fueling purposes. This eliminates a lot of unproductive driving time, which counteracts the fact that tele-remote or automated LHDs have a lower tramming speeds in general [4]. This also means that LHDs could remain productive during blasting, rather than being restricted by the potential for explosives fumes [5].


The mining industry has been acting as a leader in the development of fully autonomous vehicles in general, as the operational efficiencies that could be realized by using them is significant. Improving efficiencies in mine operations becomes amplified and results in large potential savings as a result of the scale of mining operations. Equipment manufacturers have been developing and testing autonomous vehicle technologies for a number of years. Caterpillar, Komatsu and Volvo are some of the main mining companies working on these projects, particularly on trucks. Their interests span from semi-autonomous to fully-autonomous [6].

Autonomous underground trucks have already been providing cost benefits to mining operations, as they can do onboard analysis while driving. This results in more precise and efficient route planning as compared to a manually operated vehicle, therefore reducing cycle times and operating costs. Not only is the most efficient route always selected but with the constant calculation iterations, it allows for the vehicle to change speed and gear ratios to improve efficiency in areas such as fuel economy, overall machine performance, productivity and vehicle reliability [7]. These improvements and savings are even more significant when the task is repetitive [8].

Volvo has developed the world’s first fully autonomous truck, which has been tested in operations in the Kristineberg underground mine located in Sweden. The main purpose of this truck are to improve the safety and transportation flow underground. The truck currently operates underground at a depth of 1300 meters and covers routes that total distance of 7 kilometers [6]. It operates using a various types of sensors, which allows it to continuously monitor its surroundings and avoid hazards or obstacles that are either fixed or moving. These sensors, as mentioned above, are also used to collect data and optimize the route, reducing transportation time and fuel consumption [6].

Train Transport

Transport by train is rarely used in underground mines, as the system has high capital costs. However, the Kiruna Mine is one example where it is being used in practice. . Driverless remotely controlled trains are used to transport the ore to the main level [9] [10]. The scale of the operation is enormous, as the iron orebody is approximately 80 meters wide and 4 kilometers long with an estimated 27.3 million metric tons of crude ore [11]. Therefore, an expensive system like this can be justified as a result of the large ore body

Robotic Explosives Loading

In underground mining, operators arerequired to handle explosives, including the transportation and loading of the explosives. Blast hole charging is the most common method of loading explosives in an underground mine. It requires the operator to place a primer-detonator assembly at the end of a hose and insert the hose into the blast hole. Next, emulsion is pumped into the hole, causing the primer-detonator to get pushed to the toe of the blast hole with the detonation wire remaining outside of the hole. This loading process is very dangerous, as the operator is standing at the face with little to no protection from potential premature detonation [12].

To reduce this risk, Commonwealth Scientific and Industrial Research Organization (CSIRO) aided in development efforts to create a new system which advances the automation of blast hole charging by incorporating teleoperation and robotic functionality. This effectively removes the operator from being at the face, where there is potential danger, and allows them to control the robotic loader and prepare the charges from a safe location [13]. The piece of equipment that CSIRO helped develop is capable of completing every step of the loading process, from assembling the detonator, placement in the hole and pumping of the emulsion. [12]


When it comes to underground drilling automation, the major requirement for the automated drill rig involves the “linking of surface and downhole measurements with near real-time predictive models to improve the safety and efficiency of the drilling process” [14]. The most common type of automated drilling is tele-remote. This is not a fully autonomous drill, but rather allows the possibility to have the operator somewhere other than the location of the drilling unit. This removes the operator from the potential dangers of the work face. The drills include multi angle cameras and communicates to allow for the operator to know what is taking place around the drill at all times [15]. Benefits that result from using tele-remote drilling equipment are summarized in the table below.


Currently, an issue with tele-remote drilling is that the wireless communication used for control has a set distance for optimal performance. While there is no theoretical limitation to the maximum operational distance, when operating under performance conditions that are not optimized, it can cause delays or blurry images being communicated from the rig to the operator. Common rigs require 1Mbps to work at a level accepted by operations [16].

Mapping & Surveying

Autonomous and remote vehicles have been applied to 2D and 3D mapping and surveying within mining applications, to increase surveying frequency and reduce operating costs. By frequently surveying the mine, the autonomous trucks are able to map terrain and safely navigate to their destination. Through the use of landmarks, GPS, and lasers, the autonomous vehicles are able to map the terrain despite the uneven natural surfaces found in a typical mining environment. Underground, communication is a challenge, as no GPS signal can be used for location tracking. An alternative to GPS is to track wheel movement, however this adds complication when wheel slippage occurs, or in places where the terrain is uneven [17]. Most autonomous scanning vehicles will use an inclinometer for pitch, a gyroscope for orientation, and two laser scanners for the mapping.

Safety of Autonomous Vehicles

Safety is an aspect of automation that has extremely high stakes and is one of the largest concerns voiced throughout the industry. Some companies have already integrated autonomous vehicles into their fleet and have experienced success in reducing the operating cost of their mining projects without any safety repercussions. By limiting the number of personnel near the moving equipment, there is a potential to reduce the probability of injury in the workplace. Unfortunately, this is not the only factor, as maintenance and other aspects of a mining operation require personnel underground. The integration of machines and humans in the same operation increases risk for an incident, which is amplified in a high severity environment like a mine site. As such, governments are placing strict guidelines towards the requirements on autonomous hauling systems. One example of this occurred in 2015, when the Department of Mines and Petroleum of Western Australia released a code of practice of Safe Mine Autonomous Mining [18]. Some highlights from this code of practice included: roles and responsibilities of those involved in the integration of the autonomous vehicles, risk management, training & supervision, mine planning, system planning, and hazard control.

Many autonomous vehicles have communication systems that will attempt to prevent any incidents from occurring. In most cases, these systems integrate with the light duty vehicles and auxiliary equipment in the operation. If an incident occurs, the system often has the ability to stop all vehicles under autonomous control in order for the emergency response team to review the incident. This system is extremely safe due to the nature of the shutdown mechanism, however is prone to production delays as the system may require an operator to board the vehicle and restart the system. Rio Tinto began integrating auto autonomous haul trucks in their mines in 2008 and has endured zero injuries related to the Autonomous Hauling System (AHS) [19]. By remaining in communication with other trucks and updating GPS signals including location, speed, and direction of all other connected vehicles, the trucks are able to map out routes and prevent incidents from occurring [20]. Through the use of motion sensors, the autonomous equipment is able to detect movement in front of the vehicle and stop when an unexpected obstacle is detected. The successful integration of AHS haulage in a mining application will likely continue due to their long-standing incident free record. In standard mines, haulage is responsible for a large portion of the incidents, and with the increased focus on occupational health and safety, demand for a safer haulage system is growing rapidly. In recent years, there have been new technologies developed to help notify operators of any potential issues or hazards while driving, however very few of them intervene.


In some situations, the higher capital expenditure for autonomous vehicles due to the additional systems required for navigation and the software can be justified by lowering operating costs and improving productivity after implementation. Currently, the main areas of implementation are haulage, primarily LHDs and trucks. Autonomous systems offer potential benefits such as improved operating efficiency, the smaller workforce required to operate, improved safety, and improved reliability. Disadvantages for integrating autonomous vehicles include additional capital costs and infrastructure, lower tramming speeds, reduced visibility for operators, and reduced operator feedback. The implementation of autonomous vehicles within mining applications is becoming increasingly feasible as new technology is introduced, however the variance in circumstances in the mining industry is drastic and each case will produce unique advantages and disadvantages to the implementation.


[1] V. Konyukh, "Strategy of automation for underground mining," Strategic Technology International Forum, 2007. [2] J. Marshall, A. Bonchis, E. Nebot and S. Scheding, "Mining Robotics," in Handbook of Robotics (2nd Edition), Springer, 2014. [3] S. Bandyopadhyay, S. Ghosh and A. Mandal, "Real Time Tracking and Sensing Systems for Improved Safety and Security in Mines," Indian Institute of Management , Calcutta. [4] J. Larsson, "Unmanned Operation of Load-Haul-Dump Vechicles in Mining Environments," Örebro Studies in Technology 51, 2011. [5] A. Copco, "Automation is gaining ground underground," 6 February 2018. [Online]. Available: [6] AB Volvo, "Volvo first in the world with self-driving truck in underground mine," Volvo Group, p. 3, 7 Sept 2016. [7] S. JENSEN, "The Growing Potential for Fully Autonomous Mines," OEM Off-Highway, 9 Sept 2016. [Online]. Available: [Accessed 8 Feb 2018]. [8] P. Moore, "Sandvik’s latest generation of intelligent and automated trucks," International Mining, p. 4, 2017. [9] LKAB, "Our underground mines," 5 February 2018. [Online]. Available: [10] LKAB, "LKAB," 5 February 2018. [Online]. Available: [11] LKAB, "Mining," 5 February 2018. [Online]. Available: [12] A. Bonchis, E. Duff, J. Roberts and M. Bosse, "Robotic explosive charging in mining and construction applications," Institute of Electrical and Electronics Engineers, 2014. [13] R. Crozier, "BHP Billiton hits go on autonomous drills," IT News, 20 Jun 2016. [Online]. Available: [Accessed 8 Feb 2018]. [14] SAS, "Improve drilling efficiency with predictive analytics," SAS Institute Inc, 2016. [Online]. Available: [Accessed 17 Feb 2018]. [15] Petro Wiki, "Levels of automation," SPE International, 22 Mar 2016. [Online]. Available: [Accessed 7 Feb 2018]. [16] M. Manttari, "LONG HOLE DRILLING AUTOMATION," The South African Institute of Mining and Metallurgy , Johannesburg, SA, 2015. [17] V. P. Joseph Nsasi Bakambu, "Journal of Field Robotics," 24 Oct 2007. [Online]. Available: [18] Department of Mines and Petroleum, "Department of Mines and Petroleum," 2015. [Online]. Available: [19] C. Jamasmie, "Rio Tinto Autonomous Trucks Now Hauling A Quarter of Pilbara Material," 30 Jan 2018. [Online]. Available: [20] Caterpillar, "Autonomous Haulage: Making Mining Safer and More Productive Today," 3 Oct 2014. [Online]. Available:

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