PARAMETRIC SYNTHESIS OF A MULTI-ROBOT FORMATION CONTROLLER USING THE STATISTICAL SIMULATION MODELLING
Abstract
The article proposes a parametric synthesis method of a multi-robot formation controller.
The movement of the fo m tion i c ied out on the oute et by hum n ope to . Robot’ control
system corresponds to the modular-assembly principle based on common software, the joint
functioning of which is implemented by middleware, for example, Robot Operating System. Errors in
the mobile robot control system are caused by: probabilistic application conditions, data-measuring
system random errors, using simplified dynamic model within the development process. The influence
of the operating conditions on the communication system and the mobile robot autonomous driving
system performance reflects by the probabilistic-temporal characteristics: communications and information
system delay and the inten ity of mobi e obot’ top . method of t ti tic imu tion
modeling allowed taking into account the probabilistic-temporal characteristics of the mobile robot
communication and the autonomous driving systems, as well as mobile robot dynamics. The coordinated
movement of the multi-robot formation along a given path is provided by the method of a decentralized
virtual structure. The task execution quality is evaluated by two indicators: the deviation
of the form from the given one and the task-performance time. As an example, we consider the task of
the movement of three robots along the route in a row-shaped formation, in which, for a given probabilistic-
temporal characteristics, a multi-robot formation accomplish the given task in the shortest
time with minimal deviations of formation shape from the given one. Optimization solution allowed
us to determine the optimal parameter of the formation control system. The optimization problem was
solved using the golden section method, statistical simulation was performed using MATLAB Simulink
and Parallel Computing Toolbox packages. A simulation of a homogeneous group of three
mobile robots movement was performed for the task of driving along the route in the row-shaped
formation with an interval of 5 m and a desired speed of 3 m/s. The quality of the autonomous driving
system ensures accident-free motion with an intensity of 1,2 stops per minute. The communications
and information system with fully connected network topology provides communications flow between
mobile robots with a frequency of no more than 10 Hz. Communications system delay vary in
the range from 0.1 to 0.5 s.
References
dynamic obstacles, Autonomous Robots, 2018, Vol. 42, No. 4, pp. 801-824.
2. Girard A.R. et al. A control architecture for integrated cooperative cruise control and collision
warning systems, Proceedings of the 40th IEEE Conference on Decision and Control (Cat.
No. 01CH37228). IEEE, 2001, Vol. 2, pp. 1491-1496.
3. Young S., Kott A. Control of small robot squads in complex adversarial environments: A review,
2009.
4. Nazarova A.V., Meysin' Ch. Organizatsiya spasatel'nykh komand robotov dlya likvidatsii
posledstviy stikhiynykh bedstviy [Organization of rescue teams of robots to eliminate the consequences
of natural disasters], Robototekhnika i tekhnicheskaya kibernetika [Robotics and
Technical Cybernetics], 2019, No. 1, pp. 21-28.
5. Vlasov K.S., Tachkov A.A., Danilov M.M. Taktika gruppovogo primeneniya nazemnykh
robototekhnicheskikh kompleksov pri tushenii pozharov v rezervuarnykh parkakh [Tactics of
group application of ground-based robotic complexes when extinguishing fires in tank farms],
Pozharnaya bezopasnost' [Fire Safety], 2020, No. 2, pp. 28-35.
6. Van Arem B., Van Driel C.J.G., Visser R. The impact of cooperative adaptive cruise control on
traffic-flow characteristics, IEEE Transactions on intelligent transportation systems, 2006,
Vol. 7, No. 4, pp. 429-436.
7. Sheikholeslam S., Desoer C.A. Longitudinal control of a platoon of vehicles, 1990 American
control conference. IEEE, 1990, pp. 291-296.
8. Trujillo M.A. et al. Structure Assembly, Aerial Robotic Manipulation. Springer, Cham, 2019,
pp. 351-365
9. Healey A.J. Application of formation control for multi-vehicle robotic minesweeping, Proceedings
of the 40th IEEE Conference on Decision and Control (Cat. No. 01CH37228). IEEE,
2001, Vol. 2, pp. 1497-1502.
10. Kalyaev I.A., Gayduk A.R., Kapustyan S.G. Modeli i algoritmy kollektivnogo upravleniya v
gruppakh robotov [Models and algorithms of collective management in groups of robots].
Moscow: Fizmatlit, 2009, 280 p.
11. Pshikhopov V.Kh., Medvedev M.Yu. Sravnitel'nyy analiz tsentralizovannogo i detsentralizovannogo
algoritmov dvizheniya stroem BLA mul'tikopternogo tipa [Comparative analysis of centralized and
decentralized algorithms for the movement of a multicopter-type UAV system], Izvestiya YuFU.
Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2022, No. 1 (225), pp. 121-139.
12. Tachkov A.A. [i dr.]. Printsipy postroeniya sistem avtonomnogo upravleniya dvizheniem
nazemnykh robototekhnicheskikh kompleksov spetsial'nogo naznacheniya [Principles of construction
of autonomous motion control systems for ground-based robotic complexes of special
purpose], Robototekhnika i tekhnicheskaya kibernetika [Robotics and technical cybernetics],
2022, Vol. 10, No. 2, pp. 121-132.
13. Iakovlev D.S. Collision Risk Analysis to Ensure the Safety of Autonomous Vehicle Motion Control,
2021 International Russian Automation Conference (RusAutoCon), 2021, pp. 644-649.
14. Maksimov A.A., Tachkov A.A., Malykhin A.Yu., Rudianov N.A. Podkhod k formalizatsii
takticheskoy zadachi dlya gruppy nazemnykh robototekhnicheskikh kompleksov voennogo
naznacheniya [An approach to the formalization of a tactical task for a group of ground-based
robotic systems for military purposes], Voprosy oboronnoy tekhniki. Ser. 16 [Issues of defense
technology. Series 16], 2017, No. 7-8 (109-110), pp. 88-96.
15. Kurochkin S.Yu., Tachkov A.A. Statisticheskaya imitatsionnaya model' gruppovogo dvizheniya
mobil'nykh robotov s uchetom veroyatnostno-vremennykh kharakteristik sistemy svyazi i
avtonomnogo upravleniya dvizheniem [Statistical simulation model of the group movement of
mobile robots taking into account the probabilistic and temporal characteristics of the communication
system and autonomous motion control], Ekstremal'naya robototekhnika [Extreme
robotics], 2022, Vol. 1, No. 1, pp. 123-129.
16. Tachkov A.A. [i dr.]. Realizatsiya traektornogo regulyatora nazemnogo robototekhnicheskogo
kompleksa na osnove model'nogo prognoziruyushchego upravleniya [Implementation of a trajectory
controller of a ground-based robotic complex based on model predictive control], Robototekhnika i
tekhnicheskaya kibernetika [Robotics and technical cybernetics], 2022, Vol. 10, No. 1, pp. 43-54.
17. Beard R.W., Lawton J., Hadaegh F.Y. A coordination architecture for spacecraft formation
control, IEEE Transactions on control systems technology, 2001, Vol. 9, No. 6, pp. 777-790.
18. Ren W. Consensus strategies for cooperative control of vehicle formations, IET Control Theory
& Applications, 2007, Vol. 1, No. 2, pp. 505-512.
19. Fax J.A., Murray R.M. Information flow and cooperative control of vehicle formations, IFAC
Proceedings Volumes, 2002, Vol. 35, No. 1, pp. 115-120.
20. Karpenko A.P. Sovremennye algoritmy poiskovoy optimizatsii [Modern search engine optimization
algorithms]. Moscow: Izd-vo MGTU im. N.E. Baumana, 2014, 446 p.
