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• APPLICATION OF THE MIXED PARAMETER ESTIMATION METHOD IN THE CONSTRUCTION OF A HOMOGENEOUS NESTED PIECEWISE LINEAR REGRESSION OF THE FIRST TYPE

  S.I. Noskov , А. P. Medvedev , I. D. Kirillov

  102-109

  2026-09-10

  Abstract ▼

  The paper is devoted to the development of an algorithm for identifying the parameters of a homogeneous nested piecewise linear regression of the first type – a model that is in demand when analyzing complex systems whose behavior cannot be adequately described by smooth functions. The review part of the work systematizes modern publications illustrating the use of piecewise linear forms in various subject areas: from modeling energy consumption and nonlinear control systems to image processing, reconstruction of genetic networks, and filtering of geophysical data. The novelty of the study lies in the fact that for the first time for this class of models an identification algorithm based on the mixed estimation method (MEM) is proposed, which allows flexible combination of two different quality criteria. It is shown that by introducing additional Boolean variables and auxiliary constraints, the original optimization problem is reduced to a standard linear Boolean programming problem, which makes it possible to use available numerical methods for its solution. The effectiveness of the developed algorithm is demonstrated on real data of the mining and metallurgical company Norilsk Nickel for 2010–2024. The dependent variable is revenue, and the predictors are the production volumes of nickel, palladium, copper and platinum. Two alternative models are constructed – using the classical least absolute deviations method and the proposed mixed estimation method. A comparative analysis shows that the second model has a slightly higher average percentage error, but significantly outperforms in the magnitude of the maximum error on the control subsample, which makes it preferable in conditions where outliers are critical. The results obtained confirm the practical value of MEM for constructing interpretable and robust regression dependencies

• 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

• GROUPING PREDICTORS IN COMBINED PIECEWISE LINEAR REGRESSION

  S.I. Noskov , S.V. Belyaev

  120-127

  2025-10-01

  Abstract ▼

  The article provides a brief overview of publications on the application of combined structures containing known model forms as constituent elements in mathematical modeling of complex systems. In particular, the following are considered: an algorithm for estimating parameters for creating mathematical models of dynamic systems; structured mathematical models of an oxygen electrode and biological wastewater treatment; a combined model including ion exchange between calcium and copper; a combination of non-standard finite-difference schemes and the Richardson extrapolation method to obtain numerical solutions of two models of biological systems; a mathematical formulation of the problem and a heuristic approach to optimal planning of delivery routes in a multimodal system; a mathematical model for optimizing strategic and tactical decisions in all types of biomass-based supply chains; a method for developing models of various types for elements of chemical-engineering systems taking into account various types of available information and combining these models into a single complex. Two variants of the problem statement for calculating the estimates of the parameters of a combined piecewise linear regression are formulated: with a non-empty and empty intersection of the index sets that define the composition of the independent variables in the linear and piecewise linear components of the model. It is shown that in both cases, when the sum of absolute deviations of approximation errors is selected as the loss function, both variants are reduced to linear-Boolean programming problems. Two versions of a combined piecewise linear regression model of revenue of the mining and metallurgical company Severstal are constructed. The following production volumes are used as independent variables of the model: hot-rolled, cold-rolled and galvanized sheet, sheet with another metal coating, sheet with a polymer coating, rolled products, hardware products.

• THE APPLICATION OF COMPLEX DESCRIPTORS IN SOLVING A SLAM TASK

  V. P. Noskov, А. N. Kuryanov

  2022-04-21

  Abstract ▼

  The actual problem of determining all six coordinates (three linear and three angular) of the
  current position of a mobile robot (unmanned aerial vehicle) from video rangefinder images of the
  external environment (volumetric colored point clouds) formed by an onboard integrated vision
  system built on the basis of a 3D rangefinder sensor (lidar) and a color video camera while moving
  (flying) in an unknown environment is considered. An algorithm of video navigation based on
  the use of complexed (video-rangefinder) descriptors is proposed, for the description of which
  visual and geometric parameters are used. The rules for the formation of a complex descriptor are
  formulated, which ensure the allocation of special (central) points of the descriptor using the
  Sobel operator and the calculation of brightness and geometric parameters in its local area. The
  addition of the brightness parameters of the descriptor provided by the video camera with the geometric
  parameters provided by the rangefinder sensor removes the problem of invariance of the
  descriptor to the scale and thereby significantly reduces the complexity of calculations when selecting
  it. The rules for finding complexed descriptors corresponding to each other in a sequence
  of complexed images are described, based on calculating the difference in brightness and geometric
  parameters of the compared descriptors. The estimation of the error in solving the navigation
  problem using the integrated descriptors was performed depending on the error of the sensors of
  the vision system and the geometric dimensions of the descriptor. By constructing histograms of
  the solution of the navigation problem for each coordinate of the control object for all pairs of
  descriptors corresponding to each other, a statistically stable high reliability of the solution of the
  complete navigation problem has been achieved. At the same time, the error in solving the navigation
  task turned out to be an order of magnitude smaller than the error in the formation of complex
  images by the technical vision system. The use of complex descriptors made it possible, with a
  relatively small amount of calculations, to solve the complete navigation problem with acceptable
  accuracy, which provides a solution to the SLAM problem on the onboard computations at the
  pace of movement of the control object. The effectiveness of the proposed algorithmic and developed
  software and hardware is confirmed by field experiments conducted in real conditions of
  various environments.

• DEVELOPMENT AND ANALYSE VISUAL NAVIGATION SYSTEM FOR AIR AND GROUND-BASED ROBOTS

  V. P. Noskov, Y. S. Barichev, О.P. Goydin, А.N. Kuryanov

  2025-04-27

  Abstract ▼

  The work is devoted to solving urgent problems of joint autonomous visual navigation for air and
  ground-based robots in urbanized environments. These environments are highly demanded for special
  operations, including dense urban areas and buildings, where the use of traditional remote control devices
  is limited due to the presence of shielded areas. The proposed solution addresses group navigation tasks
  based on data from onboard vision systems during operational reconnaissance of the working area by an
  unmanned aerial vehicle (UAV). The results of this reconnaissance enable autonomous movement and
  flight, both for individual heterogeneous robotic systems and for groups.The navigation algorithms are
  based on methods for extracting a horizontal reference surface and horizontal sections of the external
  environment from a volumetric point cloud generated by an onboard lidar. These methods allow for the
  precise and rapid determination of all six coordinates of the control object. Cases where the navigation
  task cannot be fully solved due to specific environmental characteristics are also considered. To address these challenges, methods are proposed to enhance lidar rangefinding data by integrating video camera
  data. An accuracy assessment of the video navigation solutions is provided, obtained through mathematical
  modeling of the external environment and the generation of video data. To ensure safe autonomous
  flight and movement of robotic systems in urban environments, methods for reducing video navigation
  errors are proposed. These methods utilize a specially designed bank of reference images with known
  coordinates of their formation. The effectiveness of the applied methods and the proposed video navigation
  algorithms is confirmed by experimental studies of the corresponding software and hardware in real
  urbanized environments

• THE PROCEDURE FOR CALCULATING THE DRIVE OF THE WORKING BODY OF A ROBOTIC DEVICE FOR HUMANITARIAN DEMINING

  S.S. Noskov, А.Y. Barannik, А.А. Lebedev, A.V. Lagutina

  2024-08-12

  Abstract ▼

  The aim of the study is to develop a methodology that allows us to calculate the main parameters
  characterizing the ability of a robotic vehicle equipped with a striker minesweeper to perform humanitarian
  demining operations. For this purpose, within the framework of this work, tasks were solved such as
  calculating the torque on the shaft of the striker trawl, determining the power of the motor driving the
  striker trawl, and calculating the power of the power plant of a robotic vehicle. During the research, the
  experience of creating and the main parameters of foreign mine clearance equipment with firing minesweepers
  were analyzed – the Hydrema 910 MCV crew mine clearance vehicle, the MV-4 robotic mine
  clearance vehicle, the Uran-6 remote-controlled mine clearance vehicle, and the MT-2 remote-controlled
  mine trawl. The main features of the working body of the considered machines, namely the firing minesweeper,
  were also analyzed. The developed methodology is based on a method for calculating the resistance
  force of soil destruction and an explosive object when exposed to a bike, based on the theory of
  interaction of working bodies of earthmoving machines, developed by academician N.G. Dombrovsky.
  Also, during the development of this technique, the results of work on the calculation of the design of the
  striker trawl were used by Croatian specialists Vinkovic N., Stojkovic V. and Mikulic D. At the same time,
  calculations were carried out for various soils, which, depending on the resistivity of cutting, are divided
  into 4 categories: sandy clay, gravel; dense clay, coal; hard clay with gravel; medium slate, chalk, soft
  gypsum stone. The obtained data actually became an array of initial information, which, together with
  known physical dependencies, allowed us to form an array of calculation formulas that allow us to calculate
  the torque on the shaft of the striker trawl, the power of the motor driving the striker trawl, as well as
  the power of the power plant of the robotic means, and thereby solve the scientific problem posed at the
  beginning of the study.

• THE INFORMATION AND NAVIGATION FIELD CONSTRUCTING SYSTEM FOR UGV AND UAV IN AN URBAN ENVIRONMENT

  Y.S. Barichev, О. P. Goydin, S.А. Sobolnikov, V.P. Noskov

  2024-04-16

  Abstract ▼

  The recent increasing demand of heterogeneous groups of robots (UAV and UGV) with increased
  autonomy when conducting special operations in industrial and urban environments is
  substantiated. The urgent task of forming, based on data from UAVs on-board computer vision
  systems, an information and navigation field that ensures autonomous targeted safe UAVs and
  UGVs movement in shielded areas of an urban environment is formulated. The formation of a
  generalized geometric model of the external environment can be achieved by specifying a set of
  target positions in terms of the working area, which the UAV must visit in a given sequence and
  return to the starting point. In the process of visiting achievable target points, a generalized geometric
  model of the external environment is formed and the current coordinates of the UAV are
  determined. Methods and algorithms for constructing various models of the external environment
  and solving navigation tasks are described, which ensure planning and executing of targeted safe
  movement trajectories in real time according to on-board data, which is the basis of autonomous
  control, including the heterogeneous robots’ groups control. Autonomous control systems for the
  movement of UAVs and UGVs are based on methods and algorithms for identifying semantic objects
  (supporting surface planes and vertical walls), which abound in urban environments, and
  extreme navigation using 3D images (point clouds), obtained from lidar or depth cameras.
  The results of experiments on the information and navigation fields creation and solving navigation
  tasks based on on-board computer vision data in a real industrial-urban environment are
  presented, confirming the effectiveness and practical value of the proposed methods and algorithms.
  The use of a single information and navigation field, on the one hand, significantly increases
  the autonomy of a group of robots due to the ability to independently plan actions when
  performing complex operations, and on the other hand, increases the situational awareness of
  robot operators by providing information about the working space in a convenient form

• CONTACT AND VISUAL BASED ENVIRONMENT CLASSIFICATION FOR MOBILE ROBOTS

  V.P. Noskov, I.V. Rubtsov, K.Y. Mashkov, A.V. Vazaev

  2021-04-04

  Abstract ▼

  To increase the capabilities and expand possible applications of robotic systems for special
  purposes, switching from the currently being adopted remote control systems to semi-autonomous
  systems that monitor operator actions and perform part of his functions is proposed. Moving to
  autonomous control systems capable of functioning in the "silent" mode, in shielded areas andbeyond the range of radio communications is proposed as a next step. Such intellectualization of
  on-board control systems will allow to eliminate fundamental limitations and disadvantages
  caused by the communication channel and ensures the implementation of robot group control. It is
  shown that the basis for robot autonomy increasing of on-board control systems, both for movement
  and tool control, is onboard environment model generation and determining the coordinates
  of the control object. External environment model and current coordinates makes it possible to
  automate the trajectory planning and movement, which ensures the autonomous functioning of
  robotic systems. The complex problem of environment segmentation according to geometric and
  ground passability is considered, taking into account the characteristics of the chassis, the geometry
  of the relief and the supporting properties of the ground. The existing methods are described
  and the results of experimental studies are given to solve the following main tasks: – classification
  of the operation zone according to geometric passability based data from the onboard technical
  vision system; – ground types recognition according to the integrated technical vision system; –
  using the apparatus of neural networks to improve the reliability of ground types recognition; –
  determination of ground reference characteristics by measuring the reactions of the chassis during
  movement. The promising directions for further research in integrating tactile and visual information
  to improve the reliability of the classification of operation zone according to the complex
  criterion of geometric and support passability are formulated.

• AUTOMATED LANDING OF AN UNMANNED HELICOPTER TO AN UNEQUPPED SITE

  N.V. Kim, V.P. Noskov, I.V. Rubtsov, V.A. Anikin

  2020-07-10

  Abstract ▼

  Unmanned helicopters perform many tasks in difficult operating conditions and are subject to various destabilizing factors that significantly affect flight safety. The main problems encoun-tered in the operation of unmanned helicopters are considered. It is shown that the insufficient level of flight safety is caused, in particular, by the high frequency of crashes during forced land-ings. The necessity of creating onboard means of automatic landing of an unmanned helicopter is proved. Taking into account the requirements of the Federal aviation regulations for landing plac-es, the parameters-restrictions that allow formalizing the choice of terrain areas suitable for land-ing according to the onboard technical vision system are formulated. On the basis of comparative analysis, it is shown that at present, when forming the initial video data for solving this problem, it is advisable to use a complex system of technical vision based on mutually adjusted and having a common viewing area of a 3D laser sensor, color video camera and thermal imager. The proposedrecognition algorithms of the pick-up location in the video data on-Board complex system of tech-nical vision with the use of geometric criteria and the reference permeability. It is proposed to perform the recognition of landing places based on the criterion of geometric cross-country capa-bility in two stages: at the first stage, a map of terrain heights is formed based on 3D laser sensor data, and at the second stage, areas suitable for helicopter landing are selected. Recognition of suitable and unsuitable areas is performed by comparing the elevation differences of this terrain with the reference elevation differences defined for this unmanned helicopter. It is proposed to perform the recognition of suitable landing sites based on the criterion of reference passability by calculating the Euclidean distance between the obtained data and pre-known standards corre-sponding to different types of soil in the six-dimensional feature space (height variance, reflected signal intensity, three colors, and temperature). The final selection of suitable places for planting is proposed to be made from sites that meet both criteria. The results of the work of the corre-sponding software and hardware in real conditions are presented, confirming the correctness and effectiveness of the proposed algorithms.