Robotics in the mining industry

working in a mining environment is associated with numerous risks. In its turn, modern industry demands more and more minerals, but rich deposits are running out. Now mining enterprises have to develop deposits with more complex mining and geological conditions. As a consequence, the risks become more dangerous and more likely to occur. In the mining industry, the number of fatal accidents is 10 times higher than the industry average. The solution to this problem could be industrial robotization. An analysis of existing robotic installations in the mining industry showed that they need to be systematized according to the degree of their autonomy. A similar challenge was already faced in the automotive industry, and the J3016 standard was created by the SAE Marketing Group in conjunction with the Technical Standards Committee. Taking into account existing examples of systematization of autonomous devices and the experience of related industries, we have developed our own analogue. Compared to existing systematizations, we proposed a refinement of this classification to reflect current solutions. After analyzing the existing robotic systems in terms of their degree of autonomy, it turned out that open-pit mining is already well-positioned for introducing the concept of a “humanless open-pit”. However, underground mining operations can only robotize some processes. This is mainly due to the lack of a GPS signal and the difficulty of conducting WI-FI and 5G LTE in mine workings.

Keywords: mining, robotics, digital, production safety, control system, mine surveying, lidar.
For citation:

Glatko Y. S., Sultimov R. V., Bondar G. E., Buttaev S. T., Malykh M. N., Myaskov A. V. Robotics in the mining industry. MIAB. Mining Inf. Anal. Bull. 2022;(10-2):147—155. [In Russ]. DOI: 10.25018/0236_1493_2022_102_0_147.

Acknowledgements:
Issue number: 10
Year: 2022
Page number: 147-155
ISBN: 0236-1493
UDK: 622
DOI: 10.25018/0236_1493_2022_102_0_147
Article receipt date: 20.03.2022
Date of review receipt: 15.07.2022
Date of the editorial board′s decision on the article′s publishing: 10.09.2022
About authors:

Glatko Y. S.1, PhD student, e-mail: yr.glatko@yandex.ru, ORCID ID: 0000-0002-9784-7632;
Sultimov R. V.1, student, e-mail: yr.glatko@yandex.ru, ORCID ID: 0000-0001-9081-2616;
Bondar G. E.1, student, researcher at Robotics laboratory e-mail: gbondartest2@yandex.ru, ORCID ID: 0000-0002-3319-9170;
Buttaev S. T.1, student, e-mail: buttaev77@gmail.com, ORCID ID: 0000-0001-7028-799X;
Malykh M. N.1, student, e-mail: m_malyx@mail.ru, ORCID ID: 0000-0002-8936-3208;
Myaskov A. V.1, Dr. Sci. (Ec.), professor, Head of NUST MISIS College of Mining, e-mail: myaskov@misis.ru, ORCID ID: 0000-0002-8520-3653;
1 National University of Science and Technology MISIS, Moscow, Russia.

 

For contacts:

Sultimov R. V., e-mail: roman.sultimov@mail.ru.

Bibliography:

1. Russian Federal State Statistics Service.URL: https://rosstat.gov.ru/ (Access date: 10.02.2022).

2. International Federation of Robotics. URL: https://ifr.org/ifr-press-releases/news/ record-2.7-million-robots-work-in-factories-around-the-globe (Access date: 10.02.2022).

3. Lösch, R., Grehl, S., Donner, M., Buhl, C., Jung, B. (2018). Design of an Autonomous Robot for Mapping, Navigation, and Manipulation in Underground Mines, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, 1407−1412. DOI: 10.1109/IROS.2018.8594190.

4. Santosh, K. N., Swetalina, P., P Raj, S. S., Ranjan, K. D. A Novel Application of Artificial Neural Network for the Solution of Inverse Kinematics Controls of Robotic Manipulators", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.9, pp.81−91, 2012. DOI: 10.5815/ijisa.2012.09.11.

5. Siberian Science News. URL: www.sib-science.info/ru/news/kemerovskie-uchenyesozdali-shagayuschego-10122020 (Access date: 10.02.2022).

6. Rosbalt. URL: https://www.rosbalt.ru/business/2018/08/27/1727556.html (Access date: 10.02.2022).

7. Shadrin, S. S., Ivanova, A. A. (2019). Analytical review of SAE J3016 "Classification, terms and definitions of automated traffic control systems for motor vehicles" with regard to recent changes. Automobile. Road. Infrastructure, 3(21), 10.

8. Isyanov, O. A., Marchev, A. S., Rabolt, A. N., Mereskin, I. V. (2019). Experience of applying the XLPD low-profile robotic loading and unloading machine during mining of low thickness strata-shaped ore bodies of a mine. Mining Industry Journal, 6, 44. DOI:10.30686/1609−9192−2019−6-148−44−48.

9. Lösch, R., Grehl, S., Donner, M., Buhl, C., Jung, B. (2018). Design of an Autonomous Robot for Mapping, Navigation, and Manipulation in Underground Mines, 2018, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1407−1412. DOI: 10.1109/IROS.2018.8594190.

10. IGrader.ru. URL:https://igrader.ru/trailers/rusbiznesavto-stala-strategicheskimpartnyorom-kassbohrer (Access date: 10.02.2022).

11. Iksmedia.ru. URL:https://www.iksmedia.ru/news/5506632-Buldozer-nadistancionnom-upravleni.html (Access date: 10.02.2022).

12. Khazin, M. L. (2020). Robotic Equipment for Mining Operations. Vestnik Magnitogorskogo Gosudarstvennogo Tekhnich-eskogo Universiteta im. G. I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University], 18, 1, 4−15. DOI: 10.18503/1995−2732−2020−18−1-4−15.

13. Vist Robotics completed the first stage of robotization of the BelAZ. URL: https:// cnews.ru/link/n413351 (Access date: 10.02.2022).

14. Robotic and remote controlled underground equipment: implementation, operation, prospects. URL: https://mining-media.ru/ru/article/podzemmash/16254-robotizirovannayai-distantsionno-upravlyaemaya-podzemnaya-tekhnika-vnedrenie-ekspluatatsiya-perspektivy (Access date: 10.02.2022).

15. Epiroc. URL: https://www.epiroc.com/ru-ru/products/drill-rigs/production-drill-rigs/ simba-m6 (Access date: 10.02.2022).

16. CAT. URL: https://www.cat.com/ru_RU/products/new/equipment/off-highwaytrucks/mining-trucks/13894258.html (Access date: 10.02.2022).

17. TechInsider. URL: https://www.popmech.ru/vehicles/10522-nechelovecheskiy-faktorroboty/ (Access date: 10.02.2022).

18. URL: https://techfusion.ru/built-robotics-sozdali-bespilotnyj-umnyj-ekskavator/(Access date: 10.02.2022).

19. Zhuravlev, A. G. (2014). Trends in the development of transport systems of quarries using robotic machines. Problems of Subsoil Use, 164−175.

20. URL: http://viewpointmining.com/article/the-caterpillar-journey-to-autonomousmining (Access date: 10.02.2022).

21. Günther, F., Mischo, H., Lösch, R., Grehl, S., Güth, F. (2019). Increased safety in deep mining with IoT and autonomous robots. DOI:10.13140/RG.2.2.15064.14087.

22. Minimum viable product (MVP). Wikipedia. URL: https://en.wikipedia.org/wiki/ Minimum_viable_product (Access date: 10.02.2022).

23. Abramyan, G. O. (2019). Estimation of geological study of a deposit area while mining planning. 19th International Multidisciplinary Scientific GeoConference SGEM, 19 (1.3), 279−284. DOI:10.5593/SGEM2019/1.3/S03.035.

24. Fedotov, G., Sapronova, N. (2021).Geological and mining information systems as a tool for digital transformation of production processes in mining companies.Mine surveying and subsurface use, 4(114), 54−59.

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