ДЕЦЕНТРАЛИЗОВАННОЕ УПРАВЛЕНИЕ ГРУППОЙ АВТОНОМНЫХ ПОДВИЖНЫХ ОБЪЕКТОВ ПРИ ФОРМИРОВАНИИ ТРАЕКТОРИИ ДВИЖЕНИЯ
Цитировать: Б. К. Лебедев , О. Б. Лебедев , М.И. Бесхмельнов. Децентрализованное управление группой автономных подвижных объектов при формировании траектории движения // Известия ЮФУ. Технические науки - 2024. - №6. - C. 177-190. doi: 10.18522/2311-3103-2024-6-177-190
Ключевые слова:
Группа беспилотных летательных аппаратов, движение строя, групповое управление, децентрализованное управление, траектория, альтернативная коллективная адаптация, объект адаптации, роевые алгоритмы
Аннотация
В статье рассматриваются алгоритмы формирования траекторий движения беспилотных
летательных аппаратов (БПЛА) при проведении поисково-спасательных и ликвидационных опера-
ций. Описаны методы и алгоритмы управления движением группы БПЛА в строю, при разверты-
вании в линию, при развертывании в шеренгу, при поворотах, в колонне. Управление осуществля-
ется с помощью альтернативных алгоритмов коллективной адаптации, основанных на идеях кол-
лективного поведения. Рассмотрены принципы функционирования одного автомата адаптации.
Целью управления ведомыми роботами является минимизация отклонений. Для реализации меха-
низма адаптации параметрам вектора сопоставляются автоматы адаптации, моделирующие
поведение объектов адаптации в среде. Разработана структура процесса альтернативной кол-
лективной адаптации параметров, под контролем которых осуществляется движение группы
БПЛА в строю. Разработаны оригинальные правила управления параметрами, обладающие рядом
преимуществ по сравнению с другими методами: полная децентрализация управления в сочетании
с динамической коррекцией параметров роботов, задающих положение и ориентация робота в
абсолютной системе координат, и линейную скорость робота соответственно. Предложена
структура маневра, выполняемого роботом для коррекции отклонений параметров. Управление
осуществляется с помощью алгоритма альтернативной коллективной адаптации, основанного на
идеях коллективного поведения объектов адаптации, что позволяет эффективно обрабатывать
внештатные ситуации, такие как выход агентов из строя, изменения числа агентов вследствие
выхода из строя или внезапного приобретения связи с очередным агентом, а также в условиях
наличия ошибок измерений и шумов, удовлетворяющих определённым ограничениям.
Литература
1. Burdakov S.F., Sizov P.A. Algoritmy upravleniya dvizheniem mobil'nogo robota v zadache
presledovaniya [Algorithms for controlling the motion of a mobile robot in a pursuit problem],
Informatika, telekommunikatsii i upravlenie [Computer Science, Telecommunications and Management],
2014, No. 6 (210), pp. 49-58.
2. Kotov D.V., Lebedev O.B. Metody i algoritmy upravleniya dvizheniem gruppy bespilotnykh
letatel'nykh apparatov [Methods and algorithms for controlling the movement of a group of unmanned
aerial vehicles], Integrirovannye modeli i myagkie vychisleniya v iskusstvennom intellekte: Sb.
nauchnykh trudov XII-y Mezhdunarodnoy nauchno-tekhnicheskoy konferentsii [Integrated models and
soft computing in artificial intelligence. Collection of scientific papers of the XII International Scientific
and Technical Conference]. Kolomna: Universum, 2024, pp. 236-248.
3. Veselov G.E., Lebedev B.K., Lebedev O.B. Upravlenie dvizheniem gruppy mobil'nykh robotov v
kolonne [Control of the movement of a group of mobile robots in a column], Nauchno-prakticheskiy
zhurnal Informatizatsiya i svyaz' [Scientific and practical journal Informatization and Communication],
2021, No. 3, pp. 7-11.
4. Veselov G.E., Lebedev B.K., Lebedev O.B. Adaptivnoe upravlenie peredvizheniem kollektiva
mobil'nykh robotov razvernutykh v liniyu [Adaptive control of the movement of a team of mobile robots
deployed in a line], Integrirovannye modeli i myagkie vychisleniya v iskusstvennom intellekte: Sb.
nauchnykh trudov X-y Mezhdunarodnoy nauchno-tekhnicheskoy konferentsii [Integrated models and
soft computing in artificial intelligence. Collection of scientific papers of the X-th International Scientific
and Technical Conference]. Smolensk: Universum, 2021, pp. 238-246.
5. Guzik V.F., Pereverzev V.A., P'yavchenko A.O., Saprykin R.V. Printsipy postroeniya ekstrapoliruyushchego
mnogomernogo neyrosetevogo planirovshchika intellektual'noy sistemy pozitsionno-traektornogo
upravleniya podvizhnymi ob"ektami [Principles of constructing an extrapolating multidimensional
neural network planner for an intelligent system of position-trajectory control of moving objects],
Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2016, No. 2 (175),
pp. 67-80.
6. Kostyukov V.A., Medvedev I.M., Medvedev M.Yu., Pshikhopov V.Kh. Chislennoe modelirovanie
roevogo algoritma planirovaniya puti v dvukhmernoy nekartografirovannoy srede [Numerical modeling
of a swarm path planning algorithm in a two-dimensional unmapped environment], Vestnik
Yuzhno-Ural'skogo gosudarstvennogo universiteta [Bulletin of the South Ural State University], 2024,
Vol. 16, No. 2, pp. 26-40.
7. Karpenko A.P. Sovremennye algoritmy poiskovoy optimizatsii. Algoritmy, vdokhnovlennye prirodoy:
ucheb. posobie [Modern algorithms of search engine optimization. Algorithms inspired by nature: a tutorial].
3rd ed. Moscow: Izd-vo MGTU im. N.E. Baumana, 2021, 448 p.
8. Kuznetsov A.V. Model' dvizheniya i vzaimodeystviya sistemy intellektual'nykh agentov [Model of
movement and interaction of a system of intelligent agents], Vestnik VGU. Seriya: Sistemnyy analiz i
informatsionnye tekhnologii [VSU Bulletin. Series: Systems analysis and information technology],
2018, No. 2, pp. 130-138.
9. Muslimov T.Z., Munasypov R.A. Detsentralizovannoe gruppovoe nelineynoe upravlenie stroem
bespilotnykh letatel'nykh apparatov samoletnogo tipa [Decentralized group nonlinear control of a formation
of aircraft-type unmanned aerial vehicles], Mekhatronika, avtomatizatsiya, upravlenie [Mechatronics,
automation, control], 2020, Vol. 21, No. 1, pp. 43-50.
10. Beloglazov D.A., Guzik V.F., Medvedev M.Yu., Pshikhopov V.Kh., P'yavchenko A.O., Saprykin R.V.,
Solov'ev V.V., Finaev V.I. Intellektual'nye tekhnologii planirovaniya peremeshcheniy podvizhnykh ob"ektov
v trekhmernykh nedeterminirovannykh sredakh [Intelligent technologies for planning the movements of
moving objects in three-dimensional non-deterministic environments]. Moscow: Nauka, 2017, 232 p.
11. Neydorf R.A., Polyakh V.V., Chernogorov I.V., Yarakhmedov O.T. Issledovanie evristicheskikh algoritmov v
zadachakh prokladki i optimizatsiya marshrutov v srede s prepyatstviyami [Study of heuristic algorithms in
problems of route planning and optimization in an environment with obstacles], Izvestiya YuFU.
Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2016, No. 3 (176), pp. 127-143.
12. Pshikhopov V.Kh. i dr. Intellektual'noe planirovanie traektoriy podvizhnykh ob"ektov v sredakh s
prepyatstviyami [Intelligent planning of trajectories of moving objects in environments with obstacles],
ed. by V.Kh. Pshikhopova. Moscow: Fizmatlit, 2014.
13. Gayduk A.R., Mart'yanov O.V., Medvedev M.Yu., Pshikhopov V.Kh., KHamdan N., Farkhud A.
Neyrosetevaya sistema upravleniya gruppoy robotov v neopredelennoy dvumernoy srede [Neural network
control system for a group of robots in an uncertain two-dimensional environment], Mekhatronika,
avtomatizatsiya, upravlenie [Mechatronics, automation, control], 2020, No. 21 (8), pp. 470-479.
14. Pshikhopov V.Kh., Medvedev M.Yu. Upravlenie podvizhnymi ob"ektami v opredelennykh i
neopredelennykh sredakh [Control of moving objects in certain and uncertain environments]. Moscow:
Nauka, 2011.
15. Ivanov D.Ya. Raspredelenie roley v koalitsiyakh robotov pri ogranichennykh kommunikatsiyakh na
osnove roevogo vzaimodeystviya [Distribution of roles in robot coalitions with limited communications
based on swarm interaction], Upravlenie bol'shimi sistemami: Sb. trudov [Control of large systems:
Collection of works], 2019, No. 78, pp. 23-45.
16. Pshikhopov V.Kh., Medvedev M.Yu., Gurenko B.V. Algoritmy adaptivnykh pozitsionno-traektornykh
sistem upravleniya podvizhnymi ob"ektami [Algorithms of adaptive position-trajectory control systems
for moving objects], Problemy upravleniya [Problems of control], 2015, No. 4, pp. 66-74.
17. Caro G.D., Ducatelle F. AntHocNet: An adaptive nature inspired algorithm for routing in mobile ad
hoc networks, European Transactions on Telecommunications, 2005, No. 16 (5), pp. 443-455.
18. Chen S., Eshaghian M.M. A fast recursive mapping algorithm. Department of computer and information
science. New Jersey, USA: New Jersey, 2013, pp. 219-227.
19. Fatemeh K.P., Reza S.N. Comparing the Performance of Genetic Algorithm and Ant Colony Optimization
Algorithm for Mobile Robot Path Planning in the Dynamic Environments with Different Complexities,
Journal of Academic and Applied Studies, 2013, Vol. 3 (2), pp. 29-44.
20. Hoefler T., Snir M. Generic Topology Mapping Strategies for Large-scale Parallel Architectures. University
of Illinois, 2011, pp. 75-85.
21. Veselov G.E., Lebedev B.K., Lebedev O.B. Management of Behavior of a Swarm of Robots Applicable
to the Tasks of Monitoring a Some Territory, Artificial Intelligence Methods in Intelligent Algorithms.
Springer, Czech Republic, 2020, Vol. 2, pp. 324-332.
22. Makarenko S.I. Robototekhnicheskie kompleksy voennogo naznacheniya sovremennoe sostoyanie i
perspektivy razvitiya [Robotic complexes for military purposes: current state and development prospects],
Sistemy upravleniya, svyazi i bezopasnosti [Control, communication and security systems], 2016, No. 2.
presledovaniya [Algorithms for controlling the motion of a mobile robot in a pursuit problem],
Informatika, telekommunikatsii i upravlenie [Computer Science, Telecommunications and Management],
2014, No. 6 (210), pp. 49-58.
2. Kotov D.V., Lebedev O.B. Metody i algoritmy upravleniya dvizheniem gruppy bespilotnykh
letatel'nykh apparatov [Methods and algorithms for controlling the movement of a group of unmanned
aerial vehicles], Integrirovannye modeli i myagkie vychisleniya v iskusstvennom intellekte: Sb.
nauchnykh trudov XII-y Mezhdunarodnoy nauchno-tekhnicheskoy konferentsii [Integrated models and
soft computing in artificial intelligence. Collection of scientific papers of the XII International Scientific
and Technical Conference]. Kolomna: Universum, 2024, pp. 236-248.
3. Veselov G.E., Lebedev B.K., Lebedev O.B. Upravlenie dvizheniem gruppy mobil'nykh robotov v
kolonne [Control of the movement of a group of mobile robots in a column], Nauchno-prakticheskiy
zhurnal Informatizatsiya i svyaz' [Scientific and practical journal Informatization and Communication],
2021, No. 3, pp. 7-11.
4. Veselov G.E., Lebedev B.K., Lebedev O.B. Adaptivnoe upravlenie peredvizheniem kollektiva
mobil'nykh robotov razvernutykh v liniyu [Adaptive control of the movement of a team of mobile robots
deployed in a line], Integrirovannye modeli i myagkie vychisleniya v iskusstvennom intellekte: Sb.
nauchnykh trudov X-y Mezhdunarodnoy nauchno-tekhnicheskoy konferentsii [Integrated models and
soft computing in artificial intelligence. Collection of scientific papers of the X-th International Scientific
and Technical Conference]. Smolensk: Universum, 2021, pp. 238-246.
5. Guzik V.F., Pereverzev V.A., P'yavchenko A.O., Saprykin R.V. Printsipy postroeniya ekstrapoliruyushchego
mnogomernogo neyrosetevogo planirovshchika intellektual'noy sistemy pozitsionno-traektornogo
upravleniya podvizhnymi ob"ektami [Principles of constructing an extrapolating multidimensional
neural network planner for an intelligent system of position-trajectory control of moving objects],
Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2016, No. 2 (175),
pp. 67-80.
6. Kostyukov V.A., Medvedev I.M., Medvedev M.Yu., Pshikhopov V.Kh. Chislennoe modelirovanie
roevogo algoritma planirovaniya puti v dvukhmernoy nekartografirovannoy srede [Numerical modeling
of a swarm path planning algorithm in a two-dimensional unmapped environment], Vestnik
Yuzhno-Ural'skogo gosudarstvennogo universiteta [Bulletin of the South Ural State University], 2024,
Vol. 16, No. 2, pp. 26-40.
7. Karpenko A.P. Sovremennye algoritmy poiskovoy optimizatsii. Algoritmy, vdokhnovlennye prirodoy:
ucheb. posobie [Modern algorithms of search engine optimization. Algorithms inspired by nature: a tutorial].
3rd ed. Moscow: Izd-vo MGTU im. N.E. Baumana, 2021, 448 p.
8. Kuznetsov A.V. Model' dvizheniya i vzaimodeystviya sistemy intellektual'nykh agentov [Model of
movement and interaction of a system of intelligent agents], Vestnik VGU. Seriya: Sistemnyy analiz i
informatsionnye tekhnologii [VSU Bulletin. Series: Systems analysis and information technology],
2018, No. 2, pp. 130-138.
9. Muslimov T.Z., Munasypov R.A. Detsentralizovannoe gruppovoe nelineynoe upravlenie stroem
bespilotnykh letatel'nykh apparatov samoletnogo tipa [Decentralized group nonlinear control of a formation
of aircraft-type unmanned aerial vehicles], Mekhatronika, avtomatizatsiya, upravlenie [Mechatronics,
automation, control], 2020, Vol. 21, No. 1, pp. 43-50.
10. Beloglazov D.A., Guzik V.F., Medvedev M.Yu., Pshikhopov V.Kh., P'yavchenko A.O., Saprykin R.V.,
Solov'ev V.V., Finaev V.I. Intellektual'nye tekhnologii planirovaniya peremeshcheniy podvizhnykh ob"ektov
v trekhmernykh nedeterminirovannykh sredakh [Intelligent technologies for planning the movements of
moving objects in three-dimensional non-deterministic environments]. Moscow: Nauka, 2017, 232 p.
11. Neydorf R.A., Polyakh V.V., Chernogorov I.V., Yarakhmedov O.T. Issledovanie evristicheskikh algoritmov v
zadachakh prokladki i optimizatsiya marshrutov v srede s prepyatstviyami [Study of heuristic algorithms in
problems of route planning and optimization in an environment with obstacles], Izvestiya YuFU.
Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2016, No. 3 (176), pp. 127-143.
12. Pshikhopov V.Kh. i dr. Intellektual'noe planirovanie traektoriy podvizhnykh ob"ektov v sredakh s
prepyatstviyami [Intelligent planning of trajectories of moving objects in environments with obstacles],
ed. by V.Kh. Pshikhopova. Moscow: Fizmatlit, 2014.
13. Gayduk A.R., Mart'yanov O.V., Medvedev M.Yu., Pshikhopov V.Kh., KHamdan N., Farkhud A.
Neyrosetevaya sistema upravleniya gruppoy robotov v neopredelennoy dvumernoy srede [Neural network
control system for a group of robots in an uncertain two-dimensional environment], Mekhatronika,
avtomatizatsiya, upravlenie [Mechatronics, automation, control], 2020, No. 21 (8), pp. 470-479.
14. Pshikhopov V.Kh., Medvedev M.Yu. Upravlenie podvizhnymi ob"ektami v opredelennykh i
neopredelennykh sredakh [Control of moving objects in certain and uncertain environments]. Moscow:
Nauka, 2011.
15. Ivanov D.Ya. Raspredelenie roley v koalitsiyakh robotov pri ogranichennykh kommunikatsiyakh na
osnove roevogo vzaimodeystviya [Distribution of roles in robot coalitions with limited communications
based on swarm interaction], Upravlenie bol'shimi sistemami: Sb. trudov [Control of large systems:
Collection of works], 2019, No. 78, pp. 23-45.
16. Pshikhopov V.Kh., Medvedev M.Yu., Gurenko B.V. Algoritmy adaptivnykh pozitsionno-traektornykh
sistem upravleniya podvizhnymi ob"ektami [Algorithms of adaptive position-trajectory control systems
for moving objects], Problemy upravleniya [Problems of control], 2015, No. 4, pp. 66-74.
17. Caro G.D., Ducatelle F. AntHocNet: An adaptive nature inspired algorithm for routing in mobile ad
hoc networks, European Transactions on Telecommunications, 2005, No. 16 (5), pp. 443-455.
18. Chen S., Eshaghian M.M. A fast recursive mapping algorithm. Department of computer and information
science. New Jersey, USA: New Jersey, 2013, pp. 219-227.
19. Fatemeh K.P., Reza S.N. Comparing the Performance of Genetic Algorithm and Ant Colony Optimization
Algorithm for Mobile Robot Path Planning in the Dynamic Environments with Different Complexities,
Journal of Academic and Applied Studies, 2013, Vol. 3 (2), pp. 29-44.
20. Hoefler T., Snir M. Generic Topology Mapping Strategies for Large-scale Parallel Architectures. University
of Illinois, 2011, pp. 75-85.
21. Veselov G.E., Lebedev B.K., Lebedev O.B. Management of Behavior of a Swarm of Robots Applicable
to the Tasks of Monitoring a Some Territory, Artificial Intelligence Methods in Intelligent Algorithms.
Springer, Czech Republic, 2020, Vol. 2, pp. 324-332.
22. Makarenko S.I. Robototekhnicheskie kompleksy voennogo naznacheniya sovremennoe sostoyanie i
perspektivy razvitiya [Robotic complexes for military purposes: current state and development prospects],
Sistemy upravleniya, svyazi i bezopasnosti [Control, communication and security systems], 2016, No. 2.
Опубликован
2025-01-19
Выпуск
Раздел
РАЗДЕЛ III. ВЫЧИСЛИТЕЛЬНЫЕ И ИНФОРМАЦИОННО-УПРАВЛЯЮЩИЕ СИСТЕМЫ
