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• 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 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