STUDY OF APPROACHES TO THE UNIFICATION OF ON-BOARD COMPUTERS
Keywords:
Onboard computers, robotics, VITA90, COM-Express, Elbrus
Abstract
Research in the field of creating specialized computing systems for robots is conducted
in many world scientific centers, including our country. The development of capabilities of
sensor systems, global navigation systems, growth of computing power and improvement of
algorithms allow creating onboard computing systems with broad intellectual capabilities.
An important, but unsolved problem remains the equipping of such computing systems with
domestically produced microprocessors. One of the difficulties hindering the widespread
integration of domestic hardware is the problem of unification and standardization of the
components of the onboard computers. Unification of onboard computer modules would open
up new opportunities for developers of robotic systems by reducing the price and simplifying
development and modernization. This article discusses approaches to the unification and
standardization of elements of onboard computers, describes the experience of the development
of ANSI/VITA standards in the field of onboard computers, and also provides examples
of computing modules in a unified COM-Express form-factor based on Elbrus microprocessors
for onboard computers. Experiments were conducted using unified computing modules based on Elbrus-2C3, Elbrus-1C+ and Elbrus-4C microprocessors. Their applicability for
creation of onboard computing complexes is shown. The necessity of developing a domestic
standard for on-board computer housings and form-factors is shown.
References
1. Romanov A.M. Obzor apparatno-programmnogo obespecheniya sistem upravleniya robotov
razlichnogo masshtaba i naznacheniya. Ch. 3. Ekstremal'naya robototekhnika [Review of
hardware and software for robot control systems of various scales and purposes. Part 3. Extreme
robotics], Rossiyskiy tekhnologicheskiy zhurnal [Russian Technological Journa], 2020,
Vol. 8, No. 3 (35), pp. 14-32. DOI: 10.32362/2500-316X-2020-8-3-14-32.
2. Bychkov I.N., Lobanov I.N., Molchanov I.A. Resheniya po vklyucheniyu sredstv zashchity
informatsii v vychislitel'nye kompleksy na osnove platformy "El'brus" [Solutions for the inclusion
of information security tools in computing complexes based on the Elbrus platform],
Nanoindustriya [Nanoindustry], 2020, Vol. 13, No. S4 (99), S. 103-104. DOI: 10.22184/1993-
8578.2020.13.4s.103.104.
3. Bocharov N.A. Programmno-apparatnaya platforma "El'brus" dlya resheniya zadach
iskusstvennogo intellekta [Software and hardware platform "Elbrus" for solving artificial intelligence
problems], Nanoindustriya [Nanoindustry], 2021, Vol. 14, No. S7 (107), pp. 638-640.
DOI: 10.22184/1993-8578.2021.14.7s.638.640.
4. Chuchko P.A., Bychkov I.N., Panchenko E.G. Problema unifikatsii moduley na osnove
protsessora "El'brus-2S3" [The problem of unification of modules based on the processor "Elbrus-
2C3"], Nanoindustriya [Nanoindustry], 2021, Vol. 14, No. S7 (107), pp. 96-97. DOI:
10.22184/1993-8578.2021.14.7s.96.97.
5. Available at: http://www.mcst.ru/e4c-com.
6. Available at: http://www.sm1820.ru/2018/09/04/mp18/.
7. Available at: http://www.sm1820.ru/2021/12/10/e2c3-com/.
8. Bocharov N.A., Zuev A.G., Slavin O.A. Proizvoditel'nost' mikroprotsessora El'brus-8SV dlya
resheniya zadach tekhnicheskogo zreniya v usloviyakh ogranicheniy energopotrebleniya [The performance
of the Elbrus-8SV microprocessor for solving problems of technical vision in conditions
of limited energy consumption], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering
Sciences], 2021, No. 1 (218), pp. 259-271. DOI: 10.18522/2311-3103-2021-1-259-271.
9. Bocharov N.A. Modelirovanie algoritmov katastrofoustoychivosti grupp robotov na
programmno - apparatnoy platforme "El'brus" [Modeling of algorithms for disaster tolerance
of robot groups on the Elbrus hardware and software platform], Radiopromyshlennost' [Radio
Industry], 2019, No. 3, pp. 8-14. DOI: 10.21778/2413-9599-2019-29-3-8-14.
10. Suman Harapanahalli, Niall O Mahony, Gustavo Velasco Hernandez, Sean Campbell, Daniel
Riordan, Joseph Walsh. Autonomous Navigation of mobile robots in factory environment, Procedia
Manufacturing, 2019, Vol. 38, pp. 1524-1531. ISSN 2351-9789. Available at:
https://doi.org/10.1016/ j.promfg.2020.01.134.
11. Pileun Kim, Jisoo Park, Yong K. Cho, Junsuk Kang. UAV-assisted autonomous mobile robot
navigation for as-is 3D data collection and registration in cluttered environments, Automation
in Construction, 2019, Vol. 106, 102918. ISSN 0926-5805. Available at:
https://doi.org/10.1016/ j.autcon.2019.102918.
12. Pieter M. Blok, Koen van Boheemen, Frits K. van Evert, Joris IJsselmuiden, Gook-Hwan Kim.
Robot navigation in orchards with localization based on Particle filter and Kalman filter,
Computers and Electronics in Agriculture, 2019, Vol. 157, pp. 261-269. ISSN 0168-1699,
https://doi.org/10.1016/j.compag.2018.12.046.
13. Vasiliki Balaska, Loukas Bampis, Moses Boudourides, Antonios Gasteratos. Unsupervised
semantic clustering and localization for mobile robotics tasks, Robotics and Autonomous Systems,
2020, Vol. 131, 103567. ISSN 0921-8890, https://doi.org/10.1016/j.robot.2020.103567.
14. Lin S. et al. A Review of Path-Planning Approaches for Multiple Mobile Robots, Machines,
2022, Vol. 10, No. 9, pp. 773.
15. Lamini, Said Benhlima, Ali Elbekri. Genetic Algorithm Based Approach for Autonomous Mobile
Robot Path Planning, Procedia Computer Science, 2018, Vol. 127, pp. 180-189. ISSN
1877-0509, https://doi.org/10.1016/j.procs.2018.01.113.
16. Haitao Zhao, Lingchu Mao, Jibo Wei. Coverage on demand: A simple motion control algorithm
for autonomous robotic sensor networks, Computer Networks, 2018, Vol. 135, pp. 190-200.
ISSN 1389-1286. https://doi.org/10.1016/j.comnet.2018.02.004.
17. Guilherme Maeda, Okan Koç, Jun Morimoto. Phase portraits as movement primitives for fast
humanoid robot control, Neural Networks, 2020, Vol. 129, pp. 109-122. ISSN 0893-6080,
https://doi.org/10.1016/j.neunet.2020.04.007.
18. Bocharov N.A., Paramonov N.B., Alexandrov A.V., Slavin O.A. Solving of tasks of cognitive
control a robots group in multi-core microprocessors "elbrus", CEUR Workshop Proceedings:
Selected Papers of the 2nd International Scientific Conference "Convergent Cognitive Information
Technologies", Convergent 2017, Moscow, 24–26 ноября 2017 года. Moscow, 2017,
pp. 234-244.
19. Bocharov N.A., Gladkikh A.S., Paramonov N.B., Senchenkov S.V. Vozmozhnosti
mikroprotsessorov El'brus-8S i El'brus-8SV dlya resheniya zadach robototekhniki [Capabilities
of Elbrus-8C and Elbrus-8SV microprocessors for solving robotics problems],
Robotizatsiya Vooruzhennykh Sil Rossiyskoy Federatsii: Sb. statey V voenno-nauchnoy
konferentsii, Anapa, 29–30 iyulya 2020 g. [Robotization of the Armed Forces of the Russian
Federation: Collection of articles of the V Military Scientific Conference, Anapa, July 29-30,
2020]. Anapa: Federal'noe gosudarstvennoe avtonomnoe uchrezhdenie "Voennyy
innovatsionnyy tekhnopolis "ERA", 2020, pp. 71-83.
20. Bocharov N.A., Paramonov N.B., Slavin O.A., Suminov K.A. Matematicheskie i programmnye
modeli zadach tekhnicheskogo zreniya robototekhnicheskikh kompleksov na osnove
mikroprotsessorov “El'brus” [Mathematical and software models of technical vision problems of robotic
complexes based on “Elbrus” microprocessors], Tr. Instituta sistemnogo programmirovaniya
RAN [Proceedings of the Institute of System Programming of the Russian Academy of Sciences],
2022, 34 (6), pp. 85-100. Available at: https://doi.org/10.15514/ISPRAS-2022-34(6)-6.
razlichnogo masshtaba i naznacheniya. Ch. 3. Ekstremal'naya robototekhnika [Review of
hardware and software for robot control systems of various scales and purposes. Part 3. Extreme
robotics], Rossiyskiy tekhnologicheskiy zhurnal [Russian Technological Journa], 2020,
Vol. 8, No. 3 (35), pp. 14-32. DOI: 10.32362/2500-316X-2020-8-3-14-32.
2. Bychkov I.N., Lobanov I.N., Molchanov I.A. Resheniya po vklyucheniyu sredstv zashchity
informatsii v vychislitel'nye kompleksy na osnove platformy "El'brus" [Solutions for the inclusion
of information security tools in computing complexes based on the Elbrus platform],
Nanoindustriya [Nanoindustry], 2020, Vol. 13, No. S4 (99), S. 103-104. DOI: 10.22184/1993-
8578.2020.13.4s.103.104.
3. Bocharov N.A. Programmno-apparatnaya platforma "El'brus" dlya resheniya zadach
iskusstvennogo intellekta [Software and hardware platform "Elbrus" for solving artificial intelligence
problems], Nanoindustriya [Nanoindustry], 2021, Vol. 14, No. S7 (107), pp. 638-640.
DOI: 10.22184/1993-8578.2021.14.7s.638.640.
4. Chuchko P.A., Bychkov I.N., Panchenko E.G. Problema unifikatsii moduley na osnove
protsessora "El'brus-2S3" [The problem of unification of modules based on the processor "Elbrus-
2C3"], Nanoindustriya [Nanoindustry], 2021, Vol. 14, No. S7 (107), pp. 96-97. DOI:
10.22184/1993-8578.2021.14.7s.96.97.
5. Available at: http://www.mcst.ru/e4c-com.
6. Available at: http://www.sm1820.ru/2018/09/04/mp18/.
7. Available at: http://www.sm1820.ru/2021/12/10/e2c3-com/.
8. Bocharov N.A., Zuev A.G., Slavin O.A. Proizvoditel'nost' mikroprotsessora El'brus-8SV dlya
resheniya zadach tekhnicheskogo zreniya v usloviyakh ogranicheniy energopotrebleniya [The performance
of the Elbrus-8SV microprocessor for solving problems of technical vision in conditions
of limited energy consumption], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering
Sciences], 2021, No. 1 (218), pp. 259-271. DOI: 10.18522/2311-3103-2021-1-259-271.
9. Bocharov N.A. Modelirovanie algoritmov katastrofoustoychivosti grupp robotov na
programmno - apparatnoy platforme "El'brus" [Modeling of algorithms for disaster tolerance
of robot groups on the Elbrus hardware and software platform], Radiopromyshlennost' [Radio
Industry], 2019, No. 3, pp. 8-14. DOI: 10.21778/2413-9599-2019-29-3-8-14.
10. Suman Harapanahalli, Niall O Mahony, Gustavo Velasco Hernandez, Sean Campbell, Daniel
Riordan, Joseph Walsh. Autonomous Navigation of mobile robots in factory environment, Procedia
Manufacturing, 2019, Vol. 38, pp. 1524-1531. ISSN 2351-9789. Available at:
https://doi.org/10.1016/ j.promfg.2020.01.134.
11. Pileun Kim, Jisoo Park, Yong K. Cho, Junsuk Kang. UAV-assisted autonomous mobile robot
navigation for as-is 3D data collection and registration in cluttered environments, Automation
in Construction, 2019, Vol. 106, 102918. ISSN 0926-5805. Available at:
https://doi.org/10.1016/ j.autcon.2019.102918.
12. Pieter M. Blok, Koen van Boheemen, Frits K. van Evert, Joris IJsselmuiden, Gook-Hwan Kim.
Robot navigation in orchards with localization based on Particle filter and Kalman filter,
Computers and Electronics in Agriculture, 2019, Vol. 157, pp. 261-269. ISSN 0168-1699,
https://doi.org/10.1016/j.compag.2018.12.046.
13. Vasiliki Balaska, Loukas Bampis, Moses Boudourides, Antonios Gasteratos. Unsupervised
semantic clustering and localization for mobile robotics tasks, Robotics and Autonomous Systems,
2020, Vol. 131, 103567. ISSN 0921-8890, https://doi.org/10.1016/j.robot.2020.103567.
14. Lin S. et al. A Review of Path-Planning Approaches for Multiple Mobile Robots, Machines,
2022, Vol. 10, No. 9, pp. 773.
15. Lamini, Said Benhlima, Ali Elbekri. Genetic Algorithm Based Approach for Autonomous Mobile
Robot Path Planning, Procedia Computer Science, 2018, Vol. 127, pp. 180-189. ISSN
1877-0509, https://doi.org/10.1016/j.procs.2018.01.113.
16. Haitao Zhao, Lingchu Mao, Jibo Wei. Coverage on demand: A simple motion control algorithm
for autonomous robotic sensor networks, Computer Networks, 2018, Vol. 135, pp. 190-200.
ISSN 1389-1286. https://doi.org/10.1016/j.comnet.2018.02.004.
17. Guilherme Maeda, Okan Koç, Jun Morimoto. Phase portraits as movement primitives for fast
humanoid robot control, Neural Networks, 2020, Vol. 129, pp. 109-122. ISSN 0893-6080,
https://doi.org/10.1016/j.neunet.2020.04.007.
18. Bocharov N.A., Paramonov N.B., Alexandrov A.V., Slavin O.A. Solving of tasks of cognitive
control a robots group in multi-core microprocessors "elbrus", CEUR Workshop Proceedings:
Selected Papers of the 2nd International Scientific Conference "Convergent Cognitive Information
Technologies", Convergent 2017, Moscow, 24–26 ноября 2017 года. Moscow, 2017,
pp. 234-244.
19. Bocharov N.A., Gladkikh A.S., Paramonov N.B., Senchenkov S.V. Vozmozhnosti
mikroprotsessorov El'brus-8S i El'brus-8SV dlya resheniya zadach robototekhniki [Capabilities
of Elbrus-8C and Elbrus-8SV microprocessors for solving robotics problems],
Robotizatsiya Vooruzhennykh Sil Rossiyskoy Federatsii: Sb. statey V voenno-nauchnoy
konferentsii, Anapa, 29–30 iyulya 2020 g. [Robotization of the Armed Forces of the Russian
Federation: Collection of articles of the V Military Scientific Conference, Anapa, July 29-30,
2020]. Anapa: Federal'noe gosudarstvennoe avtonomnoe uchrezhdenie "Voennyy
innovatsionnyy tekhnopolis "ERA", 2020, pp. 71-83.
20. Bocharov N.A., Paramonov N.B., Slavin O.A., Suminov K.A. Matematicheskie i programmnye
modeli zadach tekhnicheskogo zreniya robototekhnicheskikh kompleksov na osnove
mikroprotsessorov “El'brus” [Mathematical and software models of technical vision problems of robotic
complexes based on “Elbrus” microprocessors], Tr. Instituta sistemnogo programmirovaniya
RAN [Proceedings of the Institute of System Programming of the Russian Academy of Sciences],
2022, 34 (6), pp. 85-100. Available at: https://doi.org/10.15514/ISPRAS-2022-34(6)-6.
