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• 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

• 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