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• METHODS OF DATA COLLECTION BY UAVS WHEN MONITORING HARD-TO-REACH TERRAIN

  B.К. Lebedev , О. B. Lebedev

  2026-04-29

  Abstract ▼

  This paper proposes a methodology and method for constructing a model of the study area as a finite set of zones (sections) covering it, characterized by the fact that all sections are rectangular. The paper examines methods for forming a minimal set of sections on a large field that completely cover the accessible territory surveyed by unmanned aerial vehicle (UAV) sensors. The size, orientation, and relative positions of the sections are aimed at minimizing their survey time. In general, a route M is a sequential set of linear segments. Route M is divided into segments using a set of control points P. A methodology and algorithm for constructing an optimal UAV route based on the ant colony method have been developed. Mechanisms for controlling the UAV's movements along the route have been developed. In general, a route M is a sequential set of linear segments. A segment of the UAV's path (trajectory) over a surveyed area of territory being scanned (explored) is called a working segment, while a segment of the UAV's path (trajectory) over a non-scanned (explored) area is called a dummy segment. Generally, a route is an alternating sequence of working and dummy segments, replacing each other. A methodology and algorithm for moving an UAV between reference points of a segment corresponding to reference points have been developed. Two algorithms represent the solution search procedure: Algorithm 1, which describes the behavior of an ant colony; Algorithm 2, which describes the behavior of an agent. An adaptation unit supports the process of moving an UAV along a route in real-world conditions. The adaptation unit's task is to control the UAV's movement along a reference line along the route. The control method involves replanning the motion parameters of an unmanned aerial vehicle (UAV) moving parallel to a reference vector at each moment during flight. Adaptation of the UAV consists of adapting the control parameter values. A structure of maneuvers performed by UAVs to correct parameter deviations is proposed. The adaptation task consists of generating a sequence of adaptive actions in the adaptation machine that extremize the quality indicators of the resulting solutions (adaptation criteria). The adaptation object is a set of continuous flight control parameters: the UAV's deviation from the reference line; the angle between the UAV's motion vector and the reference line of the current segment; and the UAV's flight altitude above the current segment. Adaptation of the UAV consists of adapting the control parameter values

• AUV MOTION CONTROL FOR RECOVERY ON THE ROUTE TRAJECTORY IN THE OCCURRENCE OF FAILURES

  L.A. Martynova, M.B. Rozengauz

  2022-03-02

  Abstract ▼

  The aim of the research is to return the autonomous underwater vehicle to the route trajectory
  as soon as possible after the observation in the event of failures in the actuators that ensure
  the movement of the vehicle. The need to solve the problem is due to the fact that when the device
  overcomes distances of several thousand kilometers, its position deviates from the route trajectory due to the accumulation of the error in the reckoning of coordinates by the onboard inertial navigation
  system. As a result, the apparatus is forced to return to the route trajectory, during which a
  failure may occur in the actuators that ensure the movement of the apparatus. Previously, the
  problem was not considered in this formulation, and the approaches used in similar situations to
  unmanned aerial vehicles turned out to be unsuitable. The most typical reasons that distinguish an
  underwater vehicle from a drone are: the difference in the reasons for deviation from the route
  trajectory (inertial system for the device and the wind for the drone), lack of navigation using signals
  from satellite radio navigation systems and the inability to control its location when returning
  to the route , low maneuverability of the device in comparison with the drone. To solve the problem
  of ensuring the movement of the apparatus to the route trajectory in the event of a failure of
  the executive device, which ensures the movement of the apparatus, it is proposed to choose an
  alternative one from the number of redundant ones instead of the failed one. The choice of a backup
  device is determined, first of all, by the moment created by the device for maneuvering the apparatus
  along the course. At the same time, it is shown that, in view of the limitations on the ability
  of the backup device to provide the apparatus with the required maneuver along the course, it is
  also necessary to choose the trajectory of the apparatus when returning to the route trajectory.
  For this, five possible return methods were analyzed, differing in the dynamics of the course
  change, the length of the path, and the duration of maneuvering. Taking into account the smoothness
  of the course change for each trajectory, the most suitable actuators were determined, capable
  of ensuring the movement of the apparatus along the selected trajectory. The main criterion
  when choosing a trajectory, along with taking into account the limitations, was to minimize the
  distance traveled to the route trajectory in order to save the energy resource of the apparatus.
  After the selection of the actuator and the trajectory of the apparatus for restoration on the route
  trajectory, a sequence of calculations is presented to determine the parameters of the actuator at
  each moment of time throughout the return of the apparatus to the route trajectory. The results of
  the research made it possible to solve the problem of restoring the position of an autonomous underwater
  vehicle on the route trajectory in the shortest possible time in the event of a failure in the
  executive devices that ensure its movement.

• 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.