Robotic self-propelled tracked vehicles in combined mining systems

DOI: https://doi.org/10.30686/1609-9192-2023-2-76-82
Читать на русскоя языкеV.S. Velikanov1, V.A. Ovchinnikova1, I.A. Grishin2
1 Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russian Federation
2 Nosov Magnitogorsk State Technical University, Magnitogorsk, Russian Federation

Russian Mining Industry №1 / 2023 р. 76-82

Abstract: The challenges concerned with the increasing global demand for minerals have identified the need to upgrade and enhance not only the mining methods and systems, but also to create and apply mining machines that would ensure that the operators of these machines can be removed from the dusty, noisy and potentially dangerous environments of the underground mines. Therefore in the last decades the vector of research and development has been directed towards creating fully autonomous robotic machines that would perform the basic operations of the process cycle of mining minerals. To effectively operate in underground mines, the robotic mining machines need an on-board navigation system, which enables correct interpretation of environmental data from state-of-the-art sensors, creates traffic routes, controls the motion parameters and constantly monitors its own coordinates. In order to address this challenge, theoretical and experimental research has been carried out and theoretical provisions for designing control systems for smart robotic mining machines have been developed using a track-mounted underground drilling unit as an example. The SLAM method used in this study optimizes the path of an unmanned robotic track-mounted drill rig, maps the underground space, and determines the actual location of the machine on this map.

Keywords: minerals, mining machine, track-mounted vehicles, mineral mining, combined mining systems

Acknowledgments: This work was financially supported by the Ministry of Science and Higher Education of the Russian Federation (Project FRZU-2023–0008).

For citation: Velikanov V.S., Ovchinnikova V.A., Grishin I.A. Robotic self-propelled tracked vehicles in combined mining systems. Russian Mining Industry. 2023;(2):76–82. https://doi.org/10.30686/1609-9192-2023-2-76-82


Article info

Received: 12.02.2023

Revised: 27.03.2023

Accepted: 07.04.2023


Information about the authors

Vladimir S. Velikanov – Dr. Sci. (Eng.), Professor, Department of Hoisting and Hauling Machines and Robots, Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russian Federation, Professor, Department of Automatics and Computer Technologies, Ural State Mining University, Ekaterinburg, Russian Federation; ORCID https://orcid.org/0000-0001-5581-2733; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Valentina A. Ovchinnikova – Director, the Urals Advanced Engineering School, Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russian Federation; ORCID https://orcid.org/0000-0002-8084-3651; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Igor A. Grishin – Cand. Sci. (Eng.), Head of the Department of Geology, Mine Surveying and Mineral Processing, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russian Federation; ORCID https://orcid.org/0000-0001-8010-7542; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


References

1. Zhdaneev O.V. Ensuring technological sovereignty of the fuel and energy sectors of the Russian Federation in conditions of reduced imports of foreign technologies, equipment and services. Dr. Sci. (Eng.) diss. Moscow; 2022. (In Russ.) Available at: https://spmi.ru/sites/default/files/imci_images/sciens/dissertacii/2023/zhdaneev-dissertaciya-v-vide-nauchnogo-doklada_1.pdf

2. Zhdaneev O.V. Assessment of product localization during the import substitution in the fuel and energy sector. Economy of Regions. 2022;18(3):770–786. (In Russ.) https://doi.org/10.17059/ekon.reg.2022-3-11

3. Velikanov V.S., Dyorina N.V., Kocherzhinskaya Yu.V., Mamay N.V., Logunova T.V. The brachistochrone problem applied in the study on a conveyance descending trajectory in open pit mining. Vestnik of Nosov Magnitogorsk State Technical University. 2022;20(4):5–14. (In Russ.) https://doi.org/10.18503/1995-2732-2022-20-4-5-14

4. Benecke N., Hancock P., Weber M. Latest developments in the practice of shaft inspection. In: 16th international congress for mine surveying, Brisbane, Australia, 12–16 Sept. 2016, pp. 65–71.

5. Ananiev P.P., Meshcheryakov R.V., Kosterenko V.N., Kim M.L., Kontsevoi A.S. Control of a mobile robotic system for monitoring and inspection of underground workings. In: Kalyaeva I.A., Chernousko F.L., Prikhodko V.M. (eds) Progress of Vehicles and Systems-2018: Proceedings of the International Scientific and Practical Conference, Volgograd, October 9–11, 2018 г. Volgograd: Volgograd State Technical University; 2018, pp. 164–165. (In Russ.)

6. Velikanov V.S. On the importance of the establishment of company-specific personnel training centers on the basis of large mining corporations. Russian Mining Industry. 2015;(4):36–38. (In Russ.)

7. Velikanov V.S., Usov I.G., Abdrakhmanov A.A., Usov I.I. Modeling and optimization of mining machine operation modes with MATLAB. Gornyi Zhurnal. 2017;(12):78–81. (In Russ.) https://doi.org/10.17580/gzh.2017.12.15

8. Voronov A.Yu., Voronov Yu.E., Syrkin I.S., Nazarenko S.V., Yunusov I.F. A Review of unmanned haulage systems at open-pit mines. Ugol’. 2022;(S12):30–36. (In Russ.) https://doi.org/10.18796/0041-5790-2022-S12-30-36

9. Pevzner L.D., Kim M.L. Robotics in mining. Mining Informational and Analytical Bulletin. 2014;(1):240–251. (In Russ.)

10. Pevzner L.D., Kim M.L. Robotic equipment and systems for solving the elimination mining accidents. Mining Informational and Analytical Bulletin. 2016;(S1):215–223. (In Russ.)

11. Nagovitsyn O.V., Voznyak M.G. Impact of robotic technologies on open mining safety. Mining Informational and Analytical Bulletin. 2022;(12-1):52–62. (In Russ.) https://doi.org/10.25018/0236_1493_2022_121_0_52

12. Lebedev B.K., Lebedev O.B., Lebedeva E.M. Hybrid algorithm of situational trajectory planning under partial uncertainty. Herald of the Bauman Moscow State Technical University. Series Instrument Engineering. 2018;(1):76–93. (In Russ.) https://doi.org/10.18698/0236-3933-2018-1-76-93

13. Lipanov A.M., Artemiev V.B., Petrushin S.A., Kosterenko V.N., Mutygullin A.V., Kontsevoy S.I. et al. A concept of an unmanned self-propelled vehicle for operation in coal mines. Part 1. Russian Mining Industry. 2022;(5):52–63. https://doi.org/10.30686/1609-9192-2022-5-52-63

14. Androulakis V. Development of an autonomous navigation system for the shuttle car in underground room & pillar coal mines. Theses and Dissertations–Mining Engineering. 2021. 61. https://doi.org/10.13023/etd.2021.130

15. Pavlovsky V.E., Pavlovsky V.V. SLAM technologies for the mobile robots: state and prospects. Mekhatronika, Avtomatizatsiya, Upravlenie. 2016;17(6):384–394. (In Russ.) https://doi.org/10.17587/mau.17.384-394

16. Safiullin R.N., Afanasyev A.S., Reznichenko V.V. The concept of development of monitoring systems and management of intelligent technical complexes. Journal of Mining Institute. 2019;237:322–330. (In Russ.) https://doi.org/10.31897/pmi.2019.3.322

17. Pshikhopov V.K., Medvedev M.Yu., Krukhmalev V.A. Position-trajectory control of vehicle in 3D with point obstacles. Izvestiya SFeDU. Engineering Sciences. 2015;(1):238–250. (In Russ.)

18. Boguslavsky A.A., Borovin G.K., Kartashev V.A., Pavlovsky V.E., Sokolov S.M. Models and algorithms for smart control systems. Moscow: Institute of Applied Mathematics. M.V. Keldysh; 2019. 228 p. (In Russ.)

19. Kulchenko A.E., Lazarev V.S. Use virtual point for path-planning of vehicle in 3D. Engineering Journal of Don. 2016;(4). (In Russ.) Available at: http://ivdon.ru/ru/magazine/archive/n4y2016/382

20. Urvaev I.N. Mobile robot navigation based on laser range methods. Measurements. Monitoring. Management. Control. 2021;(1):44–51. (In Russ.). https://doi.org/10.21685/2307-5538-2021-1-5