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• DEVELOPMENT OF HEURISTIC ALGORITHMS FOR OPTIMIZING THE LOCAL TRACTORY OF UAVS BASED ON OBSTACLE AVOIDANCE PATTERNS

  L.А. Rybak , I.А. Duen , V.V. Cherkasov , А.А. Voloshkin , Т.А. Dunin

  2026-04-29

  Abstract ▼

  A key challenge in developing an information and control system for autonomous navigation of unmanned aerial vehicles (UAVs) in the absence of satellite communications is the generation of a local trajectory in the presence of obstacles (trees, power lines, etc.). The goal of this study is to develop heuristic algorithms that optimize the UAV's local trajectory using LiDAR data and construct a feasible local trajectory based on obstacle avoidance patterns. A two-stage concept is proposed: decomposing the LiDAR point cloud into oriented bounding boxes (OBBs) and generating a trajectory for traversing the OBBs using geometric patterns. The first stage implements a classic (geometric) LiDAR data processing pipeline: voxel thinning, ground plane extraction using the RANSAC method, DBSCAN clustering, and constructing bounding boxes around the clusters. This approach is implemented as a Python software module. Simulations were performed for two scenarios. The first scenario contained three obstacles, one of which was isolated, while the second and third were located in a group. The generated trajectory avoided all obstacles, with a trajectory construction time of 0.29 milliseconds. The second scenario was performed for a set of obstructions obtained by point cloud decomposition; the total number of obstacles, including the ground, was 678. [This is a fragment of the original text. The trajectory construction time in this case was 0.377 seconds. This approach provides predictable performance and a linear computational complexity estimate based on the number of obstacles, making it promising for use in autonomous navigation and UAV motion control systems

• CONTROL OF A MULTI-ROBOT SYSTEM BASED ON HIGHER-ORDER SLIDING MODES

  Nandanwar Anuj , L. А. Rybak , D. А. Dyakonov

  72-83

  2025-11-10

  Abstract ▼

  The article addresses the control problem of a second-order multi-agent robotic system with discrete time under network-induced delays. A novel approach to formation control is proposed, based on higher-order sliding mode control and cloud technologies. The interaction between agents is described using graph theory, where the Laplacian matrix  represents the communication channel between agents and the leader. The system dynamics are modeled by motion equations for the position and velocity of each agent. Special attention is paid to the impact of network-induced delays that occur during data transmission from sensors to the controller and from the controller to actuators. A multi-stage state predictor is developed, utilizing prediction methods to compensate for random delays in the network.
  The proposed control algorithm ensures rapid convergence of the system to the desired formation even in the presence of significant network delays. For each agent, a sliding surface and a reaching law are defined, taking into account multiple timestamps. A detailed stability analysis of the closed-loop system confirms the asymptotic stability of the developed control algorithm. Simulation results in MATLAB demonstrate the high efficiency of the proposed approach: a system consisting of five followers and one leader achieves the desired formation in 10.3 seconds and successfully maintains it despite random network delays. Compared to traditional first-order control methods, the new approach shows significantly improved performance, particularly in reducing chattering effects in control signals. The use of cloud technologies enables efficient real-time processing of large data volumes and implementation of complex prediction algorithms without overloading the local computational resources of the agents. The obtained results confirm the potential of the proposed approach for controlling multi-agent systems under real-world network constraints. The work also demonstrates the feasibility of using prediction methods to compensate for random packet losses and communication delays, ensuring reliable control and communication in dynamic, unpredictable scenarios

• ANALYSIS OF THE SINGULARITIES INFLUENCE ON THE FORWARD KINEMATICS SOLUTION AND THE GEOMETRY OF THE WORKSPACE OF THE GOUGH-STEWART PLATFORM

  D.I. Malyshev, L. А. Rybak, А.S. Pisarenko, V.V. Cherkasov

  2022-04-21

  Abstract ▼

  One of the obligatory requirements for parallel mechanisms design is the exclusion from the
  workspace of singularities in which the mechanism loses its controllability and malfunctions may
  occur. The analysis of the workspace of the mechanisms of a parallel structure is more complicated
  than that for the mechanisms of a serial structure, especially if the mechanism has more than
  three degrees of freedom. The article considers the problem of analyzing the influence of singularities
  on the solution of the forward kinematics and the geometry of the workspace 3/6 of the
  Gough-Stewart platform (commercial name - "Hexapod"). A numerical algorithm for solving the
  forward kinematics of platform has been developed. It is based on the direct use of the system of
  equations of the platform's kinematic constraints. Approximation of the set of solutions to the system
  of equations is based on deterministic methods of global optimization. An analysis of the
  change in the number of forward kinematics near the zone of singularities is performed. The analysis
  consists of two stages. The first stage consists in solving the forward kinematics for the position
  and orientation of the platform, at which singularities arises. The second stage consists in
  solving the forward kinematics for the case of a singularity and the case near a singularity.
  As a result of solving the forward kinematics, a different number of forward kinematics solutions
  for different cases was revealed. An algorithm has been synthesized that makes it possible to determine
  a singularity-free workspace free for given ranges of change in the platform orientation
  angles specified by Euler angles. An analysis of the dependence of the change in the volume of the
  workspace depending on the range of change in the angles of the platform orientation was carried
  out. The algorithms are implemented programmatically in the C++ programming language.
  The modeling was performed using parallel computing and the implementation of the export of
  three-dimensional models of the positions of the platform and workspace to the universal format of
  three-dimensional models STL.

• 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

• AN INTELLIGENT PLANT MONITORING AND EARLY WARNING SYSTEM BASED

  А.А. Kochkarov, А. К. Kulikov, V.А. Olkhova, А. S. Stakhmich, А.N. Rybak

  2025-04-27

  Abstract ▼

  The present study is aimed at systematizing scientific knowledge about diseases of agricultural
  crops with the subsequent integration of the data obtained into automated agricultural production management
  systems. The relevance of the work is due to the need to minimize economic losses in crop production
  through early diagnosis of pathologies and optimization of phytosanitary control. As part of the study, a classification of plant diseases was carried out.The basil plant (Ocimum basilicum L.), characterized
  by high susceptibility to phytopathogens under intensive cultivation conditions, was chosen as a model
  object. To create an automated diagnostic tool, a specialized dataset was collected, including 214 images
  of basil at various stages of vegetation. The shooting was carried out under controlled conditions
  using an RGB camera. Each sample is annotated with the localization of damage and the affected area.
  Special attention is paid to the methodological aspects of the formation of data banks for biological systems.
  It has been established that the key problems are the high variability of morphological features in
  plants, the influence of environmental factors on the visual manifestations of diseases. Based on the analysis
  of the data obtained, the architecture of the early warning system is proposed, which includes three
  modules: a sensor unit – small cameras and microclimate sensors. The algorithmic block is a neural network
  model for semantic image segmentation and algorithms for assessing the dynamics of pathology
  development. The decision – making and notification interface provides recommendations for adjusting
  irrigation regimes, applying pesticides and trace elements. The convolutional neural network is trained
  based on the YOLOv11 framework using data augmentation methods (Gaussian noise, affine transformations)
  and transfer learning. Validation of the model on the test sample showed a detection accuracy of
  74.7% (F1-score = 0.72). To reduce false positives, postprocessing of predictions has been implemented,
  taking into account the spatial and temporal correlation of the data. The developed prototype demonstrates
  the potential of integrating computer vision and agronomy to create predictive control systems.
  Further research is planned to expand the dataset and increase parametrs, as well as the introduction of
  data processing algorithms on edge devices to reduce delays in decision-making. The results obtained can
  be adapted for other indoor crops, which contributes to the development of precision agriculture and reduces
  anthropogenic stress on agroecosystems

• OPTIMAL SYNTHESIS OF THE STRUCTURE AND PARAMETERS OF A ROBOTIC SYSTEM FOR REGENERATIVE MECHANOTHERAPY BASED ON PARALLEL MECHANISMS

  L. А. Rybak, А. А. Voloshkin, V.S. Perevuznik, D.I. Malyshev

  2024-04-15

  Abstract ▼

  An analysis of the state of research has shown that currently restorative mechanotherapy is
  widely used in the rehabilitation of patients with functional disorders of the musculoskeletal system
  caused by the consequences of vascular diseases, disorders of neuroregulation of motor activity,
  injuries and pathology of the musculoskeletal system. In restorative mechanotherapy, I most
  often use robots of a sequential structure that have the necessary working area, but at the same
  time have a low load capacity, as a result of which the system has to be scaled. Parallel robots are
  an excellent solution for the implementation of mechanotherapy based on robotic tools. The article
  presents the structure and model in two versions: a single-module robotic complex (RTC) for the
  rehabilitation of one limb and a two-module robotic complex for the rehabilitation of both limbs.
  Each module includes an active 3 - PRRR manipulator to move the patient's foot and a passive
  orthosis based on an RRR mechanism to support the lower limb. Based on the clinical aspects in
  the field of rehabilitation, the requirements for the developed RTC for the rehabilitation of the
  lower limbs are formulated, taking into account the anthropometric data of patients. A mathematical
  model has been developed describing the dependence of the positions of the links of the active
  and passive mechanisms of the two modules on the angles in the joints of the passive orthosis,
  taking into account the options for attaching kinematic chains of active manipulators to mobile
  platforms and their configurations. A method of parametric synthesis of a hybrid robotic system of
  modular structure has been developed, taking into account the formed levels of parametric constraints
  depending on the ergonomics and manufacturability of the design based on a criterion in
  the form of a convolution comprising two components, one of which is based on minimizing unattainable
  trajectory points taking into account the features of anthropometric data, and the other on
  the compactness of the design. A digital RTC twin and an outboard safety mechanism as part of
  the RTC have been developed using CAD/CAE tools of the NX system. The design of the passive
  RRR mechanism was carried out by reverse engineering using 3D scanning. The results of mathematical
  modeling, as well as the results of analysis, are presented

• METHODOLOGICAL FOUNDATIONS OF DESIGNING A SIMULATOR COMPLEX FOR TRAINING DRIVERS OF VEHICLES AND SPECIAL EQUIPMENT WITH AN INTEGRATED SYSTEM OF VIRTUAL 3D MODELS OF REAL TERRAIN

  А.А. Voloshkin, L. А. Rybak, D.I. Malyshev, К.V. Chuev, V. М. Skitova

  2023-04-10

  Abstract ▼

  The development of modern training complexes for simulating vehicle control is an urgent task
  due to the high cost of control errors, which can be solved using parallel structure mechanisms.
  The article presents current research in the field of creating a model and a real prototype of a simulator
  complex for training drivers of vehicles and special equipment based on a dynamic six-degree
  mobility platform. One of the mandatory requirements when designing a platform is the exclusion
  from the working area of special positions in which the mechanism loses its controllability and malfunctions
  may occur. The article presents the results of studies of the influence of special positions on
  the solution of the direct problem of kinematics and the geometry of the working space of the Gough-
  Stewart platform (commercial name - "Hexapod"). A virtual prototype of the robotic platform was
  developed at MSC Adams, which made it possible to simulate the kinematic and dynamic parameters
  that characterize the operating conditions under the action of workloads. The greatest resultant forces
  acting on the hinges at the maximum speed that the actuator can develop are determined. In accordance
  with the ultimate load, a 3D model of the training complex was built using computer-aided
  design systems. The article presents the results of designing a training complex, a prototype is made.
  The simulator consists of an upper platform and a base, which are connected by translational electric
  drives. The driver's cabin is installed on the upper platform, which has controls similar to those of the
  car. The simulation image is displayed on the installed monitors. For the interaction and immersion
  of the driver in the simulation environment, the software and hardware complex "Route" has been
  developed, with the following functionality: – automated formation of a digital terrain model (including
  areas of urban development) based on electronic topographic maps, libraries of threedimensional
  objects, results of laser scanning of real terrain, data from mobile complexes with precision
  navigation equipment; – creation of new three-dimensional objects; – setting up a behavioral
  model of dynamic objects (intelligent agents), developed using the principles of multi-agent systems;
  – creation of sets of exercises with various emergency situations for trainees. Experimental studies of
  the prototype made it possible to evaluate its capabilities and characteristics, and adjust the algorithms.
  The research results presented in the article will contribute to the creation of a solid infrastructure,
  promoting the provision of inclusive and sustainable industrialization.