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• THE METHOD OF ESTIMATION POSITIONS OF THE UAVS BY MEASURING THE DISTANCES BETWEEN ELEMENTS OF THE GROUP

  V.A. Kostjukov, E.Y. Kosenko, M.Y. Medvedev, V.K. Pshikhopov, M.V. Mamchenko

  2021-04-04

  Abstract ▼

  Important problems in the development of mobile robotics are the task of autonomous navigation,
  automatic movement control and providing a reliable communication channel. For navigation,
  an unmanned aerial vehicle can use its own inertial navigation system and a satellite navigation
  system. The purpose of this article is to develop a method for reducing errors in the operation
  of the inertial navigation system of UAVs caused by the presence of random and systematic errors.
  In this case, we consider the situation of a monotonous increase in the systematic error over time.
  Usually, navigation data obtained from the satellite does not contain a significant systematic error
  in determining the coordinates. However, the satellite signal may be lost for a time significantly
  longer than the period of transmission of navigation data from the satellite in normal mode.
  As a result, there is a problem of increasing the accuracy of the data received from the inertial
  navigation system. This problem is particularly relevant for group application of UAVs. When
  solving group control tasks, it becomes necessary to prevent vehicle collisions and possible collisions
  already at the stage of traffic planning. In addition, to solve a number of group tasks, such as
  monitoring the terrain, conducting rescue operations, searching for objects in a given area, and
  joint cargo transportation, individual objects of the group must move smoothly in space with great
  accuracy. This imposes more stringent restrictions on the accuracy of the inertial navigation systems
  processing and the frequency of information exchange. In this paper, we propose a method
  that allows, based on data obtained from local systems that measure the mutual distances between
  objects in a group. This information allows correct the estimates of their own coordinates in such
  a way as to reduce the standard deviation of the corrected set of points from the true positions of
  objects at a given time. The method also reduces the maximum value of the corresponding deviation
  in comparison with the original set of estimates obtained from the navigation data of the INS.
  The method is demonstrated by the example of increasing the accuracy of determining global coordinates
  in a group of UAVs.

• CONEPT OF A ROBOT GROUP CALCULATION

  V.Kh. Pshikhopov, A.R. Gaiduk, M.Y. Medvedev, D.N. Gontar, V.V. Solovjev, O.V. Martyanov

  2020-07-10

  Abstract ▼

  The problem of calculation of an autonomous robotic group in order to destroy the detected enemy group is considered. A group of robots must be formed in such a way that the task assigned to it to destroy the enemy group is performed with a high degree of probability. The task is solved as an assignment problem. The initial information for solving this problem are types and numberof objects of the detected enemy group, positions of the enemy objects, information about the war possibilities of the tools available in our group, the type of group being formed (robotic or mixed), the purpose of the operation, the actions of the group at the end of the operation. We propose a solution to the problem based on the evaluation of the effectiveness of individual robotic systems. The solution is formulated as a sequence of the four stages. At the first stage, the calculation of a priori effectiveness of each element of the detected enemy group is performed. At the second stage, based on expert assessments, the choice of efficiency coefficients for each of the available robotic systems against each element of the detected enemy group is made. At the third stage, a priori estimates of the effectiveness of the available robotic systems are corrected, taking into account the coefficients selected at the second stage. At the fourth stage, a group of robotic systems is formed in such a way that its total application efficiency exceeds the total application efficiency of the detected enemy by 2.0–2.5 times. The proposed method of forming a group allows you to cre-ate both quantitative and qualitative composition of the group. The article provides an example of the formation of a group whose goal is to neutralize an exposed enemy.

• COMPARATIVE ANALYSIS OF CENTRALIZED AND DECENTRALIZED ALGORITHMS FOR THE MOVEMENT OF MULTICOPTER-TYPE UAVS

  М.Y. Medvedev, V.K. Pshikhopov

  2022-04-21

  Abstract ▼

  The development of robotics makes their group application relevant for solving various
  tasks. The effectiveness of performing the tasks of detecting and determining the coordinates of
  objects by a group of robots significantly depends on the accuracy of maintaining a given formation.
  In this regard, the task of determining motion planning algorithms that ensure the greatest
  accuracy of maintaining a given formation is of practical interest. This article is devoted to the
  study of the accuracy of maintaining the formation of a multicopter-type UAV group using a centralized
  motion planning algorithm and a decentralized algorithm. The centralized algorithm uses
  a master UAV, which transmits its coordinates to the slave UAVs. Based on the coordinates obtained
  and the given framework of the formation, the guided UAVs plan their movement. In a decentralized
  system, neighboring UAV groups transmit their coordinates to each other, on the basis
  of which the movement of a separate UAV is planned. The accuracy of the control system is investigated
  depending on the errors of the navigation system and the frequency of updating data on the
  position of the leading or neighboring UAVs. It is assumed that the group's UAVs determine their coordinates in discrete moments of time using an external navigation system. Centralized and
  decentralized algorithms are worked out by the same motion control system. The algorithms are
  investigated in this article by numerical modeling methods. In the process of simulation, models of
  kinematics, dynamics and actuators are taken into account, as well as models for the formation of
  errors in the navigation system. It is shown that the de-centralized algorithm of group motion
  planning provides higher accuracy compared to the centralized algorithm. However, the technical
  implementation of a decentralized algorithm is more complicated from the point of view of organizing
  a group communication system. In a centralized system, data transmission from the master
  UAV to the slave should be implemented. In a decentralized system, it is required to implement
  network communication.

• MODEL AND ALGORITHM OF OPERATIONAL PLANNING OF LOGISTIC PROCESSES OF TIMELY DELIVERY OF CARGO WITH THE INTERACTION OF A GROUP OF ROBOTIC COMPLEXES

  Е.D. Grigoreva, V.А. Ushakov

  2025-04-27

  Abstract ▼

  The purpose of the study is to improve the quality of operational planning (program control) of logistics
  processes in the conditions of modern urban systems with the interaction of a group of robotic systems.
  The quality of management in this study will be assessed by the number of deliveries completed after
  established directive deadlines. The goal set during the study is decomposed into the following tasks: system
  analysis of the current state of research in the field of metropolitan logistics, implementation of a
  substantive and formal formulation of the problem of operational planning of logistics processes in a metropolis
  using a group of robotic complexes, development of a model and algorithm for operational planning
  of logistics processes in a metropolis using a grouping of robotic complexes, development of special
  model-algorithmic support and its software prototype for solving the problem of operational planning of
  logistics processes in a metropolis using a grouping of robotic complexes. Proactive (anticipatory) management
  of a group of robotic systems when solving transport and logistics problems in a metropolis within the framework of the “Smart City” concept allows increasing the economic efficiency of cargo delivery.
  The article examines the scientific and technical problem of synthesizing technologies (plans) for the timely
  delivery of small-sized cargo using a group of robotic systems. The scientific significance lies in the
  application of the concept of integrated (system) modeling and proactive (anticipatory) management, and
  the practical significance lies in ensuring timely delivery of goods using a group of robotic complexes in a
  metropolis. The article discusses an example of solving the problem of operational planning of logistics
  processes using the example of Innopolis using the characteristics of Yandex delivery robots (as robotic
  complexes). During the study, an analysis of various options for objective functions was carried out: maximizing
  profit and minimizing delivery time; profit maximization; minimizing time; minimizing the number
  of robotic systems. The following indicators were chosen to evaluate the results obtained: total profit from
  deliveries; the number of deliveries not delivered on time and the total number of completed orders.
  The most suitable objective functions for solving the problem are time minimization or simultaneous time
  minimization and profit maximization. In addition, the conclusion provides directions for further research

• A GENETIC ALGORITHM FOR PLANNING THE TRAJECTORY OF A GROUP OF MOBILE ROBOTS IN THE PRESENCE OF STATIONARY AND MOBILE OBSTACLES

  L. А. Rybak, D.I. Malyshev, D. А. Dyakonov, А. А. Mamchenkova

  2025-04-27

  Abstract ▼

  The article discusses a trajectory planning method for a group of mobile robots that ensures safe
  movement and eliminates the possibility of collisions both between the robots themselves and with external
  obstacles, including moving objects. The developed mathematical model considers three main collision
  scenarios: intersection of robot trajectories within the group, interaction with stationary obstacles, and the probability of collision with moving objects. Each of these scenarios is analyzed in detail to ensure
  maximum safety during movement, and their consideration allows for efficient adaptation of robot routes
  to changing environmental conditions. The trajectory of each robot is represented as a piecewise linear
  path with intermediate points, which are optimized to ensure safe movement. Special attention is paid to
  speed adaptation on different segments of the trajectory: a robot can adjust its speed based on current
  conditions to minimize the risk of collisions. To evaluate distances between objects, the Euclidean norm is
  used, allowing for the calculation of minimum distances between the centers of spherical representations
  of robots and obstacles. The problem is solved in two stages. In the first stage, a trajectory is constructed
  for the first robot, taking into account initial conditions and obstacle placement. In the second stage, trajectories
  are formed for the remaining robots, considering the already planned routes. For optimizing the
  coordinates of intermediate points and speeds, a genetic algorithm is applied, which minimizes travel time
  while ensuring safe movement. The genetic algorithm uses crossover and mutation operators to generate
  diverse solutions and performs checks to ensure compliance with safety conditions. Numerical simulations
  were conducted using Python, with the Matplotlib library used for visualization of results. During the
  experiments, 50 tests were performed with varying numbers of obstacles (from 5 to 10). Analysis of the
  results showed that as the number of obstacles increased, both the computation time and the quality of the
  generated trajectories improved. This confirms the effectiveness of the proposed method for controlling
  groups of mobile robots in dynamically changing environments

• HYBRID METHOD FOR SOLVING THE MULTI-AGENT TRAVELING SALESMAN PROBLEM

  V.А. Kostyukov, F.А. Houssein

  2025-04-27

  Abstract ▼

  In this research work, the problem of task allocation in a multi-agent system is considered, where
  each agent is a robot, and each task is represented by a position, which should be visited by one agent.
  This problem is very similar to the multi-agent traveling salesman problem, which, unlike the famous traveling
  salesman problem, involves several traveling salesmen who visit a given number of cities exactly
  once and return to the starting position with minimal travel costs. Therefore, the multi-agent traveling
  salesman problem is analyzed as a representative of the task allocation problem. The multi-traveling
  salesman problem is important for the field of route optimization and task allocation between several
  agents. It includes two different, but interrelated subproblems: distribute cities among agents and determine
  the order in which each agent visits cities. In the literature, there are 3 concepts for solving this
  problem with respect to solving its two constituent subproblems: the optimization concept, where both
  subproblems are solved simultaneously; The Cluster-First, Route-Second concept is where the question of
  which tasks to assign to which salesman is first decided, and then the question of the order in which each
  salesman solves his tasks is decided; The Route-First, Cluster-Second concept is where the question of the
  order in which tasks should be visited is first decided, and then this cycle is divided between agents without
  changing the order of visits in order to answer the question of which tasks each agent takes on. This
  paper proposes a hybrid approach to solving the multiple traveling salesman problem (mTSP), which
  combines the ideas of two well-known concepts: "First clustering, then routing" and "First routing, then
  clustering" in order to obtain their positive aspects and get rid of their weaknesses. To evaluate the effectiveness
  of the developed method, a comparative study was conducted using the classical method for solving
  the multi-traveling salesman problem. The results were evaluated based on three key criteria: the
  computational time to obtain a solution to the multi-travelling salesman problem, the total length of the
  routes travelled by the salesmen, and the maximum route length among them. The analysis of the experimental
  data showed that when using the proposed method, the maximum path length among the routes
  travelled by the agents (load imbalance) is reduced by an average of 26%.

• DETERMINATION OF TARGET COORDINATE ERRORS IN MULTI-POSITION RADAR USING GROUPS OF UNMANNED AIRCRAFT

  I.V. Borisov , А.S. Kuzmenko , V. Е. Kuryan , Е. М. Levchenko , М.V. Kuryan

  273-284

  2025-07-24

  Abstract ▼

  The article proposes and develops an algebraic method for determining the coordinates of targets and their errors as part of a group of unmanned aerial vehicles. The main assumptions of the developed model of the functioning of a group of unmanned aerial vehicles: The speeds of aircraft do not exceed the speed of sound in the air, and the speeds of targets do not exceed the first space were justified. The main assumptions of the model of operation of a group of unmanned aerial vehicles: the UAV speeds do not exceed the speed of sound in the air, and the target speeds do not exceed the first space one, are justified in the article. Qualitative estimates of the radar signal reception time for a given spatial error of the target coordinates were presented. The conditions for the number of aircraft in the group are formulated, which increase the accuracy of determining the location of the target in space. The various types of errors that arise when organizing the search for targets by a group of aircraft are analyzed. The issues of dependence of the resulting error in calculating the coordinates of the search target on the error in measuring the distance between the aircraft in the group and the target itself, depending on their mutual spatial orientation, are investigated. An algorithm has been developed, calculations and analysis of the results for this task have been carried out. The simulation is based on the proposed algorithm, taking into account random coordinates of the target in a fixed sector and taking into account random errors in the measured distance between a group of aircraft and the search object. The results of modeling the influence of the configuration of a group of unmanned aerial vehicles and the location of the target on the error in determining its coordinates are presented. An assessment was carried out to determine the coordinates of the goals and an error estimate of the proposed algebraic approach. The ways of further research are determined. The issues of estimating the amount of calculation for a large number of goals are considered.
  The scope and effectiveness of the proposed algorithm and method for solving the problem as a whole are determined.

• ESTIMATION OF REALIZABILITY OF SOLVING TASKS ON COMPUTER SYSTEMS IN GROUP MAINTENANCE

  V.А. Pavsky, К.V. Pavsky

  2022-11-01

  Abstract ▼

  The increase in the performance of computer systems (CS) is associated with both scalability
  and the development of the architecture of the computing elements of the system. Cluster CS,
  which are scalable, make up 93% of the Top500 supercomputers and are high-performance. At the
  same time, there is still the problem of efficient and complete use of all available computer resources
  of the supercomputer and CS for solving user tasks. Failures of elementary machines
  (nodes, computing modules) reduce the technical and economic efficiency of CS and the efficiency
  of solving user tasks. Therefore, when planning the process of solving problems, reducing the loss
  of time to restore CS from failures is an important problem. To quantify the potential capabilities
  of computer systems, indices of the realizability of solving tasks are used. These indices characterize
  the quality of the systems, taking into account reliability, time characteristics and service parameters
  of incoming tasks. The paper proposes a mathematical model of the functioning of a
  computer system with a buffer memory for group maintenance of a task flow. The mathematical
  model uses queuing theory methods based on probability theory and systems of differential equations.
  It should be noted that the method of composing systems of differential equations is simpleenough if the corresponding graph scheme is presented. However, the exact solution of systems of
  equations and, as a rule, in elementary functions, does not exist, or formulas are difficult to see.
  Here the solution is obtained in the stationary mode of operation of the queuing system. The indices
  allowing to estimate the fullness of the buffer memory are calculated. The obtained analytical
  solutions are simple, can be used for express analysis of the functioning of computer systems.

• THE FORMALIZED APPROACH TO SYNTHESIS OF ARCHITECTURE IN THE SYSTEM OF ADAPTIVE GROUP CONTROL OF ROBOTIC COMPLEXES IN THE CONDITIONS OF THE NONDETERMINISTIC DYNAMIC ENVIRONMENT

  V.V. Sviridov

  2022-05-26

  Abstract ▼

  The rapid development of "multi-agent systems" as an independent and multifaceted section
  of artificial intelligence attracts many researchers in various fields of activity. The pace of progress
  in the development of information technologies, distributed information systems, and computer
  technology determines the possibilities of using robotics technologies in the Armed Forces of
  the Russian Federation. The factors presented in the article authorize the need to introduce new
  intelligent technologies into the troops - autonomous robotic complexes (systems). The development
  of artificial intelligence methods makes it possible to take a new step towards changing the
  style of interaction of complexes with each other as part of a robotic system. The idea of creating
  so-called "autonomous complexes" arose, which gave rise to a new style of adaptive group management.
  Instead of interaction initiated by the user-operator through commands and direct manipulations,
  complexes are independently involved in the joint process of solving a common problem
  in a non-deterministic dynamic environment. The article proposes a formalized approach to
  the design of architectures for group interaction of autonomous robotic complexes in a system
  based on the law of open control, i.e. induced and reliable preferences of each complex for action,
  satisfying the conditions of perfect coordination of their activities, by identifying parameters at
  which the objective function is maximized in various modes of functioning of the robotic system. A
  formalized formulation of the problem of synthesis of the adaptive group control system of autonomous
  robotic complexes under conditions of a priori uncertainty is presented. The architecture of
  group interaction of complexes is adaptively built based on the conditions of the external environment
  and the internal state of the system, in which each complex of the group functions to achieve
  a common goal (solving a system problem) at the time under consideration.

• UAV GROUP MANAGEMENT WHEN WORKING OUT OF CRISIS FLIGHT SITUATIONS IN SOLVING TRANSPORT PROBLEMS

  А.I. Savelyev, V.V. Lebedeva, I.V. Lebedev, К.V. Kamynin, L.D. Kuznetsov, А.L. Ronzhin

  2022-04-21

  Abstract ▼

  The relevance of the development of algorithms for managing a group of UAVs in the event of
  crisis situations that affect the performance of the task is substantiated. An algorithm for autonomous
  collective (decentralized) control of a group of UAVs is described when performing the target task of
  transporting goods, as well as combined control in the event of crisis situations when the autonomouscontrol mode cannot be fully implemented. The algorithm for working out a crisis situation in case of a
  lack of energy resources on board the UAV and the return of group agents to the starting position is
  described in detail. The results of modeling the movement of a group of UAVs of multirotor and aircraft
  types and working out a crisis situation for managing a group of UAVs based on information about the
  reserves of energy or fuel resources are presented. During the experiment, iteratively calculated the
  remaining fuel when the UAV moved to the landing point, as well as the amount of fuel available to the
  UAV at a given time. As a result of the experiments, it was found that the time for calculating the balance
  of the energy resource does not exceed 6.792 ms. If the leader runs out of fuel, the cargo transportation
  mission ends ahead of schedule, since it cannot be completed without the participation of the
  leader. If several slaves fail, the mission can be continued if their number does not exceed a predetermined
  value, which is critical for the continuation of the cargo delivery mission. The results of experimental
  studies on modeling the flight of an UAV with a load are presented, during which a flight route
  was built that simulates a curvilinear trajectory of movement in urban conditions from the starting point
  to the end point, where the UAV is landing and transferring the cargo. In the experiments, the developed
  UAV and the onboard fastening system of the thermal container were used. During flight tests, the average
  horizontal speed of the UAV was set to 10 m/s. The length of the flight was 5350 m. The flight time
  was 13 minutes. 51 seconds.

• THE ESTIMATION OF CHANGING ENVIRONMENTAL CONDITIONS INFLUENCE ON THE WORKLOAD DISTRIBUTION IN THE UAV GROUP

  I.B. Safronenkova, A.B. Klimenko

  2021-12-24

  Abstract ▼

  The paper considers the problem of workload distribution in a group of unmanned aerial vehicles
  (UAVs) when monitoring a certain area in a changing environment, which has a direct impact on the
  onboard energy resources consumption. The stage of a monitoring problem-solving, which includes the
  distribution of UAVs over scanning bands, is described here. When this stage is carried, there is no
  opportunity to take into account the factors of environmental impact. But these factors are crucial
  due to the limited onboard energy resources. In this regard, a situation is very likely when the UAV is
  not able to complete the sub-task assigned to it, which jeopardizes the completion of the entire mission
  of the group. To avoid this situation, it is proposed to use the technique of a decision-making on
  the need to relocate the workload in a group of mobile robots (MR). The decision-making is based on
  the ontological analysis procedure, which allows limiting the number of choices for workload relocation.
  The ontology model of the workload distribution in a group of UAVs was developed. This model
  takes into account the possibility of additional performance involvement either by means of the resources
  of neighboring UAVs, or by means of devices of the "foggy" layer. Examples of production
  rules are given, on the basis of which a decision is made on the need to relocate the workload. A
  comparative estimation of the resources volume involved in the implementation of two methods of
  workload relocation problem solving, depending on the frequency of changes in environmental conditions,
  is carried out. The results of computational experiments have shown that the method based on
  ontological analysis is more efficient in comparison with the method based on LDG (Local Device
  Group) in terms of the amount of resources involved. This makes it possible to increase the time of joint
  mission implementation by the UAV group.

• METHODOLOGY FOR ANALYZING THE FAULT SAFETY OF SYSTEMS AND AGGREGATES OF A MULTI-AGENT GROUP OF AIRCRAFT

  A.S. Boldyrev, A.L. Verevkin, L.C. Verevkina

  2022-01-31

  Abstract ▼

  Areas of application of CALS technologies are considered to be: improvement of activities
  in the field of heterogeneous processes occurring at all stages of the life cycle (LC) of products;
  supply chain management throughout the entire LC of products (from the creation of the product
  concept to its disposal); electronic integration of organizations (enterprises) involved in these
  processes at various stages of LC; management of support for LC products One of the most relevant
  areas of development in the aviation industry are: multi-agent technologies for improving the
  efficiency of aircraft (aircraft of various types in a group and a single mission) and CALS technologies.
  The article proposes a methodology for analyzing the fault safety of systems and aggregates
  of the multi-agent group of aircraft as a whole, by types of aircraft, their systems, and aggregates.
  The methodology is given on the example of statistical data of AP and PAP 16 systems: flight navigation,
  exhaust, ignition, fuel, control, power supply, air conditioning; hydraulic, radio communication
  equipment, control devices, and aggregates: engine, propellers, wings, windows, lantern,
  ten aircraft AN-2, L-410, Yak-40, An-24, Tu-134, Yak-42, Tu-154, IL-62, IL-62M, IL-86. In the
  proposed methodology for analyzing statistical data of AP and PAP, transformations with matrices
  are used, which allow not to be limited to the number of systems, aggregates, and the aircraft
  themselves. The operating time before the functional failure of systems and aggregates by types of
  aircraft was calculated, the average probability of functional failure of each of the systems and
  aggregates in a multi-agent group was determined, and the time before the functional failure of a
  multi-agent group of 10 aircraft as a whole, which was 132.5 hours, and it was determined that
  PAP and AP are more likely to occur with the chassis and engine of the aircraft. The given methodology
  allows: to correlate quantitative reliability requirements for systems and aggregates,
  taking into account random factors and uncertainty factors; to assess the feasibility of the established
  reliability requirements; to conduct a comparative analysis and justification of the choice of
  a rational variant of the composition of the aircraft group.

• MACHINE LEARNING MODEL OF SWARM EVASION FROM THE INFLUENCE OF ANTAGONISTIC ENVIRONMENT

  V. К. Abrosimov, G.А. Dolgov, Е. S. Mikhailova

  6-19

  2025-04-27

  Abstract ▼

  One of the priority areas of group control theory for the near future is swarm control of groups of
  small unmanned aerial vehicles - micro-, mini- and nano-classes, performing a collective task under enemy
  influence. Here, two antagonistic strategies collide - minimization of losses from the point of view of
  the attacking swarm and maximization of such losses from the point of view of the defense system. Research objective: development of an approach to solving a practical problem - penetration of a swarm of
  unmanned aerial vehicles into an object protected by a defense system. The objectives of the study were to
  analyze the characteristics of the factors influencing the processes of detection, tracking, recognition of
  swarm intentions by the defense system and the development of a machine learning model for creating
  spatio-temporal formations that minimize the number of swarm elements affected by the defense system.
  The main parameters of the defense system are the detection range and duration of swarm recognition, the
  time to make a decision on the actions of the swarm, the size of the zone of destruction of defense means.
  The method of machine learning on convolutional neural networks with reinforcement was chosen as the
  research method. The counteraction effect against the defense system is created due to the swarm's dynamics;
  it can actively maneuver, creating spatio-temporal maneuvers during the mission. To simulate the
  "Swarm vs. Defense System" situation, a swarm agent (a neural network with a transformer architecture
  that initiates swarm formations) and a defense system agent are introduced that recognizes the swarm and
  attacks it, creating a zone of destruction in the conventional center of mass of the swarm. The swarm is
  guided by a stochastic rule, asking the defense system (environment) to react to its maneuver. The environment
  responds by attacking the swarm, creating a damaging factor at the point where the swarm or the
  main part of the swarm is expected to be. The reward of the swarm strategy is the number of undestroyed
  objects under the conditions of constraints; for the defense system, this "reward" acts as a "punishment".
  An interesting phenomenon was established in the process of machine learning: each swarm element,
  remaining within a given space and implementing the biological principles of swarm control without a
  Leader, independently evades the area of destruction, which together creates a random spatio-temporal
  formation for defense means with minimal losses of swarm elements. Thus, using the method of machine
  learning with reinforcement, a model was created that allows varying the behavior of the swarm and synthesizing
  spatio-temporal formations that complicate detection, tracking, recognition of intentions and
  decision-making on the impact of the defense system on a swarm of attacking small unmanned aerial vehicles,
  as well as significantly reducing their losses.

• SPECIAL MODELS, ALGORITHMS AND SOFTWARE FOR PROACTIVE GROUP BEHAVIOR CONTROL OF ROBOTS

  O.V. Kofnov, S.A. Potriasaev, B.V. Sokolov, P.M. Trefilov

  2021-04-04

  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.

• METHOD FOR DETECTING FEATURE POINTS OF AN IMAGE USING A SIGN REPRESENTATIONS

  A. N. Karkishchenko, V. B. Mnukhin

  2020-11-22

  Abstract ▼

  The aim of the study is to develop a method for detecting feature points of a digital image
  that is stable with respect to a certain class of brightness transformations. The need for such a
  method is due to the needs of detecting feature points of images in video surveillance systems and
  face recognition, often working in a changing light environment. A feature of the proposed method
  that distinguishes it from a number of well-known approaches to the problem of distinguishing
  characteristic points is the use of the so-called sign representation of images. In contrast to the
  usual defining of a digital image by a discrete brightness function, with a sign representation, the
  image is set in the form of an oriented graph corresponding to the binary relation of the increase
  in brightness on a set of pixels. Thus, the sign representation determines not a single image, but a
  set of images, the brightness functions of which are connected by strictly monotonic brightness
  transformations. It is this property of the sign representation that determines its effectiveness for
  solving the problems caused by the goal set above. A feature of the method under consideration is
  a special approach to the interpretation of the characteristic points of the image. This concept in
  image processing theory is not strictly defined; we can say that the characteristic point is characterized
  by increased "complexity" of the image structure in its vicinity. Since the sign representation
  of the image can be represented in the form of a directed graph, in this paper, to evaluate the
  complexity measure of the local neighborhood of its vertices, it is proposed to use the ranking
  method known in the spectral theory of graphs based on the Perron-Frobenius theorem. Its essence
  lies in the fact that the value of the component of the so-called Perron eigenvector of the
  adjacency matrix of this graph acts as a measure of the complexity of the vertex. To conduct experimental
  studies of the proposed approach, a set of programs was developed, the results of
  which confirm the efficiency of the method and demonstrate that with its help it is possible to obtain
  results close to the expected ones on model examples. The paper also offers a number of recommendations
  on the use of this method.

• METHODOLOGY AND RELIABILITY MODELING OF THE GROUP CONTROL SYSTEM FOR ROBOTIC PLATFORMS

  A. S. Boldyrev, A. L. Verevkin, K. V. Pshikhopova , L. S. Verevkina

  2020-10-11

  Abstract ▼

  One of the most relevant areas of robotics development is the design of group cont rol
  systems. In the proposed structure, a group of five robotic platforms (RP) is controlled from a
  wearable or stationary remote control. This composition of the group determines schemeswith tunable connections between the components and changes in the principles of operation.
  The article presents experimental studies of the computational efficiency of methods for planning
  RP trajectories in space and defines the optimal method and the required parameters of
  the RP computer. Variants of schemes with different numbers of RP are considered, as well
  as models of cold backup of RP, remote controls, and the entire system. With such a variety
  of configurations, problems arise in justifying and selecting calculation methods, and in
  providing an unambiguous, generalized representation of the reliability parameters of a
  group control system. Increased requirements for the reliability of components of the group
  management system require an accurate assessment of reliability and are dictated by the
  significant cost of equipment and functional purpose. The developed method is intended for
  modeling the reliability of the developed system of group control of robotic platforms RP.
  The proposed method shows the use of structural, probabilistic and matrix methods for ca lculating
  reliability models of a group control system. An approach to modeling the reliabi lity
  of integer, redundant, sliding, and cold redundancy of RP and control panels is also pr oposed.
  The results of numerical calculations of the reliability parameters of the group management
  system allow us to assess the risks and choose modes, depending on the required
  efficiency of the mission.

• METHOD OF SPATIAL-TEMPORAL DIVERSITY OF TRAJECTORIES OF A GROUP OF ROBOTS IN THE CONTEXT OF OBSTACLES

  V.А. Kostyukov

  92-102

  2025-10-01

  Abstract ▼

  When developing algorithms for planning the paths of robots forming a group, the problem of ensuring that they do not collide with each other and with possible obstacles arises. In addition, the group may be required to maintain a given formation template in those sections of the group's movement where this is possible taking into account obstacles. However, a narrow spatial corridor of permissible movement of the group is often formed, which can be caused by both the initial requirements for the trajectory (for example, the condition of its location in a certain vicinity of a given point), and the presence of obstacles and other interference effects. The presence of such a restrictive corridor can lead to a forced convergence and even intersection of the spatial trajectories of movement of individual robots in the group. One possible solution to this problem is to specify or adjust the time parametric representations of these individual trajectories so that two robots with spatial trajectories approaching each other are at their closest points at different times. Moreover, the time interval separating the moments of these two robots being at these points should be selected depending on the speed of the robots and their dimensions. The developed method of space-time separation of the trajectories of individual robots in a group is based on this idea. The method involves the formation and solution of a special linear programming problem relative to the target moments of time of previously selected nodes of the spatial trajectory of each slave robot. The limiting factor for changing these moments is the maximum possible speed of the robot. For each robot, a preliminary selection of a set of trajectories of other robots in the group is made, from which it is then necessary to detach in space-time. This occurs depending on the priority of the robots in the group. Examples of numerical implementation of the algorithm based on the proposed method are given, confirming its effectiveness

• DEVELOPMENT OF A METHOD FOR SOLVING THE PROBLEM OF TASK ALLOCATION IN A MULTI-AGENT SYSTEM

  V.А. Kostyukov , F.А. Houssein

  144-155

  2025-10-01

  Abstract ▼

  This paper considers the problem of task distribution within a multi-agent system, where each agent is an autonomous robot, and each task corresponds to a point in a two-dimensional environment that one of the agents must visit. This problem is essentially similar to a multi-agent version of the classical traveling salesman problem, where several agents are involved instead of one participant. Each of them must go through a unique route covering a certain set of points. In this regard, a study of the multi-agent traveling salesman problem is conducted as one of the formats for setting the problem of distributing goals among agents. This problem is of great importance in the field of routing and optimal task distribution. Its solution includes two closely related subproblems: determining the set of points assigned to each agent and constructing the optimal route for visiting them. There are three main approaches to solving this problem in the scientific literature: Optimization approach, where both subproblems are solved jointly; Cluster-First, Route-Second model, where tasks are first distributed among agents, and then routes are built;
  The Route-First, Cluster-Second model assumes initial optimization of the route for all points with its subsequent division between agents without changing the order of visits. In this paper, a hybrid method is proposed that combines elements of the Cluster-First, Route-Second and Route-First, Cluster-Second approaches. The goal is to combine the strengths of both concepts and minimize their drawbacks. To test the effectiveness of the developed method, a comparative study was conducted. The evaluation was carried out according to three main metrics: the time spent on constructing a solution, the total length of all routes, and the maximum route length among all agents. The experimental results showed that the use of the proposed method allows for a reduction in the maximum route length (thereby reducing the load imbalance between agents) by an average of 26%.

• CLUSTERING ALGORITHM FOR LARGE GROUPS OF EXPERTS BASED ON THE INTERPRETIVE STRUCTURAL MODELING METHOD

  Е.М. Gerasimenko , P.S. Gerasimenko

  6-21

  2025-12-30

  Abstract ▼

  This article presents an algorithm for achieving consensus in social networks during large‑scale group decision‑making with incomplete probabilistic fuzzy information containing elements of uncertainty, which takes into account the trust relationships among experts. A method for clustering experts based on interpretive structural modelling is proposed. It serves both to classify experts and to enhance the efficiency of consensus achievement.The study examines trust propagation and aggregation operators for probabilistic fuzzy information with elements of uncertainty. These operators enable indirect trust assessment and determination of experts’ weight coefficients. As a result, it becomes possible to form several subsets of experts and to determine weight coefficients for a large number of experts based on their mutual trust relationships. Based on the clustering of experts and the calculated indirect trust relationship between experts, decision‑making in emergency situations is carried out by achieving consensus, taking into account fluctuating probabilistic fuzzy information, and the best evacuation alternative is identified.
  The assessments provided by experts in the form of probabilistic fluctuating fuzzy values allow for effective modelling of doubts, uncertainty, and inconsistencies in expert evaluations when a group of experts or various expert organisations are involved. At the same time, it becomes possible to take into account different expert assessment values in multi‑criteria decision‑making tasks when experts cannot agree on common membership degrees. The algorithm allows classifying a large group of experts into several subsets based on their social trust relationships. This method prevents the formation of overlapping subsets and does not require pre‑setting clustering parameters. It relies exclusively on social trust relationships between experts, thereby avoiding the issue of subjective intervention in the clustering process. Compared to traditional clustering methods, the interpretive structural modelling‑based clustering approach effectively reveals the hierarchical structure of relationships among experts. It also minimizes the number of participants in large‑scale group decision‑making within a social network by reducing the dimensionality of the expert set. Clustering experts based on the interpretive structural modelling method significantly enhances the efficiency and feasibility of large‑scale group decision‑making

• GROUP VIDEO NAVIGATION OF HETEROGENEOUS ROBOTS

  V.P. Noskov , О.P. Goydin , А.N. Kuryanov

  2026-04-29

  Abstract ▼

  This paper addresses the pressing challenges of collaborative autonomous video navigation of unmanned aerial vehicles and ground robots in urban environments, including dense urban development and buildings, as well as in rugged terrain, including mountainous and wooded areas, where, as in urban environments, the use of traditional remote control and navigation tools may be limited by the presence of shielded areas. It is proposed to solve group navigation problems using data from an onboard vision system during operational reconnaissance of the work area by an unmanned aerial vehicle. The results ensure autonomous movement and flight of both individual heterogeneous robotic systems and in a group. The navigation algorithms are based on the methods and algorithms for processing data from the onboard vision system, consisting of a complex of mutually adjusted lidar, television camera and thermal imager, which form the geometry of the surrounding space in the form of a point cloud with the distribution of color and temperature fields on it, allowing for the effective solution of the SLAM problem (determination of the current coordinates of the control object with the formation of a geometric model of the external environment) and the classification of the working area according to the criteria of geometric and support cross-country ability, which ensures autonomous flight and movement of robots for air and ground use in urbanized environments and on rough terrain. It is proposed to use an information and navigation field, represented as a visibility graph, to organize the autonomous operation of aerial and ground robots, including in a group, and a set of reference images, allowing for the correct execution of planned trajectories, taking into account errors in the video navigation task. This information and navigation field allows for the compact presentation of information necessary and sufficient for the autonomous operation of unmanned aerial vehicles and ground robots and facilitates its exchange between group members. The results of experimental studies in real-world conditions of urbanized environments and rugged terrain are presented, confirming the effectiveness of the proposed methods, algorithms, and corresponding software and hardware

• MODELS OF SEAMLESS OPERATION OF A GROUP OF AGRICULTURAL UAVS

  А.I. Saveliev , А.V. Ryabinov , А.V. Semenov

  2026-04-29

  Abstract ▼

  The introduction of groups of unmanned aerial vehicles (UAVs) into precision farming is hampered by several problems related to the stability of communications in areas remote from the take-off point and dependence on weather conditions, which can reduce the effectiveness of the technology. Existing planning models are insufficiently adaptive to dynamic changes in the agricultural environment, communication problems, and in most cases assume strict adherence to fixed trajectories. The purpose of this study is to develop conceptual models of seamless operation and a communication system for coordinating a group of agricultural UAVs. The paper presents a diagram of the connectivity of the system elements, which ensures the continuity of processes from initialization to automatic battery replacement and UAV refueling. A communication model of the system with the relay node has been developed that separates traffic, which makes it possible to eliminate collisions and stabilize data exchange over distances of more than 2.5 km. A method for distributing tasks, considering the energy supply and spatial coordinates of the UAV, is presented, which allows dynamically redistributing the load in case of failures. The proposed solutions enhance the autonomy and fault tolerance of the UAV group, minimize operator involvement, and ensure safe mission performance in a non-deterministic environment.
  The approbation of the proposed model, performed in laboratory and field conditions, showed its stability when transmitting data over extended distances and in group operation. The absence of collisions during data exchange between UAVs has been separately confirmed, which indicates the correctness of traffic separation and the effectiveness of the chosen communication architecture. The results obtained confirm the possibility of practical application of the developed models to increase the autonomy and continuity of agricultural work.
  The developed approach also demonstrates the potential for scaling, which expands the scope of its application in precision farming tasks.

• RESONANT EXCITATION OF BUSH NONLINEAR NORMAL MODES IN TWO-DIMENSIONAL LATTICES

  I.S. Burlachenko , G.М. Chechin

  191-201

  2026-09-10

  Abstract ▼

  This paper addresses the problem of resonant excitation of bushes in two-dimensional lattices with discrete symmetry. A bush is defined as a set of vibrational modes that persists over time and constitutes an exact solution to the nonlinear equations of motion, which cannot be obtained within the framework of perturbation theory. The relevance of this study lies in the fact that the proposed scheme for bush excitation, in contrast to previous mathematical models aimed at exciting bushes of nonlinear normal modes, can be implemented in a physical experiment. The above-mentioned ensembles of vibrational modes are considered within the framework of the theory of Chechin and Sakhnenko, based on group-theoretic research methods, which makes it possible to use any models of interatomic interaction potentials with equal success. This, in turn, allows us to consider dynamic systems of multiple scales, from molecular vibrations to the movement of macroscopic crystal structures. The aim of the work is to present a mathematical model of excitation of stable nonlinear dynamic objects in two-dimensional molecular structures suitable for both computational and physical experiments. Providing the results of a computational experiment with a description of the detected dynamic objects. Unlike traditional methods, Bush theory provides a solid theoretical framework based on group theory that overcomes the limitations of perturbation theory, offering results of exceptional reliability. At the same time, the symmetry properties used in Bush theory can provide significant advantages for numerical modeling, significantly reducing computational complexity. Now, this issue is being investigated by many authors around the world. It is worth noting, however, that the works in which the problems of excitation of dynamic objects close to the concept of bouches are discussed relate only to one-dimensional cases and that group-theoretic methods are not considered in them, with very rare exceptions

• DEVELOPMENT OF A HYBRID METHOD FOR PLANNING THE MOVEMENT OF A GROUP OF MARINE ROBOTIC COMPLEXES IN AN A PRIORI UNKNOWN ENVIRONMENT WITH OBSTACLES

  А.М. Maevsky, R.O. Morozov, А. Е. Gorely, V.A. Ryzhov

  2021-04-04

  Abstract ▼

  The article discusses the problem of organizing the group movement of marine robotics
  (MRS), in particular, unmanned autonomous underwater vehicles (AUV), in an a priori unknown
  environment with obstacles. A brief analysis of existing projects on the subject of MRS group control,
  and path-planning algorithms have been carried out. The presence of numerous studies in
  this area confirms the relevance of the indicated problem. The formal statement of the problem of
  the movement of four robots in formation is presented. The proposed method for a group path
  planning is based on a combined approach that organizes a multi-level solution to organizing the
  movement of MRS. At the upper level, a system for global path planning and mission control was
  developed based on the random tree method, which provides the general movement of the group
  based on a priori information about the state of the environment. The lower-level planning system
  adjusts the global path, allowing objects at the local level to carry out the group agents’ movement
  and interaction, including ensuring their collision-free movement in environment and exit from the
  areas of local minima. The article provides a detailed analytical description of the developed algorithm
  and a block diagram of its functioning. Numerical simulation of the movement of a group
  of 4 AUVs in a non-deterministic environment with fixed obstacles is carried out. The simulation
  was carried out taking into account obstacles of various shapes and complexity. The results of
  mathematical modeling demonstrated the solution to the problem of the exit of the AUV group
  from the area of the local minimum. Full-scale tests are presented on the example of a group of
  three unmanned boats: a group of mobile objects formed a formation and carried out a movement
  in a given formation to target positions and returned to the final zone. In addition, the local planning
  module developed within the framework of this article was integrated into the software of the
  "Shadow" underwater glider control system. In the conclusion, the results of the proposed method
  and its further development, in particular, its application in 3D environment, are considered.