SPECIAL MODELS, ALGORITHMS AND SOFTWARE FOR PROACTIVE GROUP BEHAVIOR CONTROL OF ROBOTS
Keywords:
Robots, proactive control, OODA loop, group behavior, logical-dynamic model, Behavior- Based Systems
Abstract
The paper describes the proactive control of robots group behavior using Behavior-Based System
models, where the intellect is formed by a physical entities behavior. The observed complex is an
array of distributed agents functioning in real time under disturbances. John Boyd’s OODA loop
model is used to describe the control system work cycle of such network object. The input data of the
control task are a planning horizon, a group action scenario, an array of agents and their possible
elementary operations, a set of scenarios using restrictions and a quality indicator of the controlproblem solution. The output data is the distribution plan of agents in space and time to realize the
scenario under restrictions. The developed technology predicts the environmental disturbances. The
complex predictive modeling methodology for a self-organized robots group control is used with
logical-dynamic models. One of the key advantages of developed combined models, methods, algorithms
and software is the possibility to coordinate analytical and simulation control models of complex
dynamic objects and their logical-algebraic analogs and models based on intelligent information
technology. This coordination is on the conceptual, model-algorithmic, information and software
detailing levels. The special language for modeling, planning, proactive monitoring and control
task description is also developed. This language can be used for dialog interaction, calculation
planning and data mining too. The proposed method main advantage is the non-isolated, but integrated
solving of robotics configuration (reconfiguration) modeling, planning and management with
the structural dynamics proactive control common problem solution.
References
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opisaniya geometricheskikh ob"ektov [Cognitive technologies in the problem of reducing the
dimension of the description of geometric objects], Informatsionnye tekhnologii i vychislitel'nye
sistemy [Information technologies and computational systems], 2008, No. 2, pp. 6-19.
15. Ivanova E.P., Chernova S.S. Snizhenie razmernosti slozhnykh geometricheskikh ob"ektov pri
nalichii chastnykh parametricheskikh modeley [Reducing the dimension of complex geometric
objects in the presence of private parametric models], Iskusstvennyy intellekt i prinyatie
resheniy [Artificial intelligence and decision-making], 2009, No. 3, pp. 53-58.
16. Bukhanovskiy A.V., Koval'chuk S.V., Mar'in S.V. Intellektual'nye vysokoproizvoditel'nye
programmnye kompleksy modelirovaniya slozhnykh sistem: kontseptsiya, arkhitektura i
primery realizatsii [Intelligent high-performance software complexes for modeling complex
systems: concept, architecture, and Implementation examples], Izvestiya vuzov.
Priborostroenie [Izvestiya vuzov. Instrumentation], 2009, Vol. 52, No. 10, pp. 5-24.
17. Ivanov S.V., Bukhanovskiy A.V. Analiz neopredelennosti predskazatel'nogo modelirovaniya
slozhnykh sistem: usvoenie dannykh i ansamblevye tekhnologii [Uncertainty analysis of predictive
modeling of complex systems: data assimilation and ensemble technologies], Izvestiya
vuzov. Priborostroenie [Izvestiya vuzov. Instrumentation], 2013, Vol. 56, No. 12, pp. 66-68.
18. Pavlov A.N., Kulakov A.Yu., Potryasaev S.A., Sokolov B.V. Metody, algoritmy i tekhnologii
rekonfiguratsii bortovykh sistem malomassorazmernykh kosmicheskikh apparatov [Methods,
algorithms and technologies of reconfiguration of onboard systems of small-mass-sized spacecraft],
Izvestiya vuzov. Priborostroenie [Izvestiya vuzov. Instrumentation], 2018, Vol. 61,
No. 7, pp. 596-603.
19. Kalinin V.N., Sokolov B.V. Multiple-model description of control processes for air-spacecrafts,
Journal Computer System Science International, 1996, No. 6, pp. 192-199.
20. Kalinin V.N., Sokolov B.V. Optimal planning of the process of interaction of mov-ing operating
objects, Int. J. Differ. Equ., 1985, Vol. 21, pp. 502-506.
21. Nauchno-tekhnicheskiy otchet (promezhutochnyy) po teme “Razrabotka tekhnologii i sozdanie
eksperimental'nykh programmnykh kompleksov upravleniya konfiguratsiey bortovykh sistem
malomassogabaritnykh KA v interesakh povysheniya ikh zhivuchesti” (shifr “TekhnologiyaSG-3.3.3.1”) [Scientific and technical report (interim) on the topic "Development of technology
and creation of experimental software systems for controlling the configuration of onboard
systems of small-mass spacecraft in the interests of increasing their survivability” (code"
Technologia-SG-3.3.3.1”)]. Saint Petersburg: SPIIRAN, 2018, 450 p.
22. Kokorin S.V., Potryasaev S.A., Sokolov B.V. Kombinirovannyy metod planirovaniya operatsiy
i raspredeleniya resursov sistemy upravleniya aktivnymi podvizhnymi ob"ektami [Combined
method of planning operations and resource allocation of the active mobile objects management
system], Izvestiya vuzov. Priborostroenie [Izvestiya vuzov. Instrumentation], 2012,
Vol. 55, No. 11, pp. 17-22.
23. Potryasaev S.A. Kompleksnoe modelirovanie slozhnykh protsessov na osnove notatsii BPMN
[Complex modeling of complex processes based on BPMN notation], Priborostroenie [Instrumentation],
2016, No. 11, pp. 913-920.
intellektual'nykh agentov real'nogo vremeni [Formal model of advanced interactive planning
of actions of intelligent real-time agents], XIV natsional'naya konferentsiya po iskusstvennomu
intellektu s mezhdunarodnym uchastiem KII-2014 (24-27 oktyabrya 2014 g., Kazan', Rossiya):
Tr. Konferentsii [XIV National Conference on Artificial Intelligence with International participation
CII-2014 (October 24-27, 2014, Kazan, Russia): Proceedings of the conference].
In 3 vol. Vol. 1. Kazan': Izd-vo RITS «Shkola», 2014, pp. 323-333.
2. Gorodetskiy V.I., Samoylov V.V., Trotskiy D.V. Bazovaya ontologiya kollektivnogo
povedeniya avtonomnykh agentov i ee rasshireniya [Basic ontology of collective behavior of
autonomous agents and its extensions], Izvestiya RAN. Teoriya i sistemy upravleniya [Izvestiya
RAS. Theory and control systems], 2015, No. 5, pp. 102-121.
3. Fedunov B.E. Intellektual'nye agenty v bazakh znaniy bortovykh operativno-sovetuyushchikh
ekspertnykh sistemakh tipovykh situatsiy funktsionirovaniya antropotsentricheskogo ob"ekta
[Intelligent agents in the knowledge bases of on-board operational-advising expert systems of
typical situations of functioning of an anthropocentric object], Izvestiya RAN. Teoriya i sistemy
upravleniya [Izvestiya RAS. Theory and control systems], 2019, No. 6, pp. 90-102.
4. Fedunov B.E. Bortovye intellektual'nye sistemy takticheskogo urovnya dlya antropotsentricheskikh
ob"ektov [On-board intelligent systems of the tactical level for anthropocentric objects]. Moscow:
De`Libri, 2018, 246 p.
5. Gorodetskiy V.I., Serebryakov S.V., Trotskiy D.V. Sredstva spetsifikatsii i instrumental'noy
podderzhki komandnogo povedeniya avtonomnykh agentov [Means of specification and instrumental
support of command behavior of autonomous agents], Izvestiya YuFU [Izvestiya
SFedU], 2011, No. 3, pp. 116-133.
6. Okhtilev M.Yu., Sokolov B.V., Yusupov R.M. Intellektual'nye tekhnologii monitoringa i
upravleniya strukturnoy dinamikoy slozhnykh tekhnicheskikh ob"ektov [Intelligent technologies
for monitoring and controlling the structural dynamics of complex technical objects].
Moscow: Nauka, 2006, 410 p.
7. Mikoni S.V., Sokolov B.V., Yusupov R.M. Kvalimetriya modeley i polimodel'nykh kompleksov
[Qualimetry of models and polymodel complexes]. Moscow: RAN, 2018, 314 p.
8. Okhtilev M.Yu., Sokolov B.V., Yusupov R.M. Teoreticheskie i tekhnologicheskie osnovy
kontseptsii proaktivnogo monitoringa i upravleniya slozhnymi ob"ektami [Theoretical and
technological bases of the concept of proactive monitoring and management of complex objects],
Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2015,
No. 1 (162), pp. 162-174.
9. Okhtilev M.Yu., Mustafin N.G., Miller V.E., Sokolov B.V. Kontseptsiya proaktivnogo upravleniya
slozhnymi ob"ektami: teoreticheskie i tekhnologicheskie osnovy [The concept of proactive management
of complex objects: theoretical and technological foundations], Izvestiya Vuzov.
Priborostroenie [Izvestiya Vuzov. Instrumentation], 2014, Vol. 57, No. 11, pp. 7-15.
10. Averin G.V., Zvyagintseva A.V., Shvetsova A.A. O podkhodakh k predskazatel'nomu
modelirovaniyu slozhnykh sistem [On approaches to predictive modeling of complex systems],
Nauchnye vedomosti Belgorodskogo gosudarstvennogo universiteta. Seriya
«Ekonomika. Informatika» [Scientific Bulletin of the Belgorod State University. Series" Economy.
Informatics"], 2018, Vol. 45, No. 1, pp. 140-148.
11. Kuleshov A.P. Kognitivnye tekhnologii v adaptivnykh modelyakh slozhnykh ob"ektov [Cognitive
technologies in adaptive models of complex objects], Informatsionnye tekhnologii i vychislitel'nye
sistemy [Information technologies and computing systems], 2008, Issue 1, pp. 18-29.
12. Kuleshov A.P. Tekhnologiya bystrogo vychisleniya kharakteristik slozhnykh tekhnicheskikh
ob"ektov [Technology of fast calculation of characteristics of complex technical objects],
Informatsionnye tekhnologii [Information technologies], 2006, Issue 3, pp. 4-11.
13. Bernshteyn A.V., Kuleshov A.P. Postroenie ortogonal'nykh nelineynykh mnogoobraziy v
zadachakh snizheniya razmernosti [Construction of orthogonal nonlinear manifolds in dimension
reduction problems], Tr. VII Mezhdunarodnoy shkoly-seminara «Mnogomernyy
statisticheskiy analiz i ekonometrika». Tsakhkadzor, 2008 [Proceedings of the VII International
School-Seminar "Multidimensional Statistical Analysis and Econometrics". Tsakhkadzor,
2008], pp. 25-27.
14. Bernshteyn A.V., Kuleshov A.P. Kognitivnye tekhnologii v probleme snizheniya razmernosti
opisaniya geometricheskikh ob"ektov [Cognitive technologies in the problem of reducing the
dimension of the description of geometric objects], Informatsionnye tekhnologii i vychislitel'nye
sistemy [Information technologies and computational systems], 2008, No. 2, pp. 6-19.
15. Ivanova E.P., Chernova S.S. Snizhenie razmernosti slozhnykh geometricheskikh ob"ektov pri
nalichii chastnykh parametricheskikh modeley [Reducing the dimension of complex geometric
objects in the presence of private parametric models], Iskusstvennyy intellekt i prinyatie
resheniy [Artificial intelligence and decision-making], 2009, No. 3, pp. 53-58.
16. Bukhanovskiy A.V., Koval'chuk S.V., Mar'in S.V. Intellektual'nye vysokoproizvoditel'nye
programmnye kompleksy modelirovaniya slozhnykh sistem: kontseptsiya, arkhitektura i
primery realizatsii [Intelligent high-performance software complexes for modeling complex
systems: concept, architecture, and Implementation examples], Izvestiya vuzov.
Priborostroenie [Izvestiya vuzov. Instrumentation], 2009, Vol. 52, No. 10, pp. 5-24.
17. Ivanov S.V., Bukhanovskiy A.V. Analiz neopredelennosti predskazatel'nogo modelirovaniya
slozhnykh sistem: usvoenie dannykh i ansamblevye tekhnologii [Uncertainty analysis of predictive
modeling of complex systems: data assimilation and ensemble technologies], Izvestiya
vuzov. Priborostroenie [Izvestiya vuzov. Instrumentation], 2013, Vol. 56, No. 12, pp. 66-68.
18. Pavlov A.N., Kulakov A.Yu., Potryasaev S.A., Sokolov B.V. Metody, algoritmy i tekhnologii
rekonfiguratsii bortovykh sistem malomassorazmernykh kosmicheskikh apparatov [Methods,
algorithms and technologies of reconfiguration of onboard systems of small-mass-sized spacecraft],
Izvestiya vuzov. Priborostroenie [Izvestiya vuzov. Instrumentation], 2018, Vol. 61,
No. 7, pp. 596-603.
19. Kalinin V.N., Sokolov B.V. Multiple-model description of control processes for air-spacecrafts,
Journal Computer System Science International, 1996, No. 6, pp. 192-199.
20. Kalinin V.N., Sokolov B.V. Optimal planning of the process of interaction of mov-ing operating
objects, Int. J. Differ. Equ., 1985, Vol. 21, pp. 502-506.
21. Nauchno-tekhnicheskiy otchet (promezhutochnyy) po teme “Razrabotka tekhnologii i sozdanie
eksperimental'nykh programmnykh kompleksov upravleniya konfiguratsiey bortovykh sistem
malomassogabaritnykh KA v interesakh povysheniya ikh zhivuchesti” (shifr “TekhnologiyaSG-3.3.3.1”) [Scientific and technical report (interim) on the topic "Development of technology
and creation of experimental software systems for controlling the configuration of onboard
systems of small-mass spacecraft in the interests of increasing their survivability” (code"
Technologia-SG-3.3.3.1”)]. Saint Petersburg: SPIIRAN, 2018, 450 p.
22. Kokorin S.V., Potryasaev S.A., Sokolov B.V. Kombinirovannyy metod planirovaniya operatsiy
i raspredeleniya resursov sistemy upravleniya aktivnymi podvizhnymi ob"ektami [Combined
method of planning operations and resource allocation of the active mobile objects management
system], Izvestiya vuzov. Priborostroenie [Izvestiya vuzov. Instrumentation], 2012,
Vol. 55, No. 11, pp. 17-22.
23. Potryasaev S.A. Kompleksnoe modelirovanie slozhnykh protsessov na osnove notatsii BPMN
[Complex modeling of complex processes based on BPMN notation], Priborostroenie [Instrumentation],
2016, No. 11, pp. 913-920.
Published
2021-04-04
Issue
Section
SECTION II. CONTROL AND SIMULATION SYSTEMS
