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• VISUAL NAVIGATION OF UNMANNED AERIAL VEHICLES USING SEMANTIC TERRAIN DESCRIPTIONS

  N.V. Kim, N. V. Udalova, N. Е. Bodunkov, D.S. Girenko, N.А. Lyapin

  2025-04-27

  Abstract ▼

  The article addresses the problem of visual navigation for unmanned aerial vehicles (UAVs), which
  involves the automatic determination of the current position of the UAV (coordinates in the ground (local)
  coordinate system) based on the comparison and identification of descriptions of the current images (CI)
  received on board with reference descriptions stored in the form of a digital map in the memory of the
  UAV's onboard computer. The aim of this work is to improve the efficiency of visual navigation methods in
  terms of increasing computational performance, robustness, and accuracy of image identification algorithms
  in complex and changing observation conditions by using semantic descriptions of observed scenes.
  In this work, semantic descriptions are understood as descriptions that include classes of objects observed
  in the scene, their attributes, and relationships between them. The preparation of semantic descriptions of
  the map is carried out at the pre-flight preparation stage of the UAV using pre-trained neural networks for
  semantic segmentation. Semantic descriptions of the received CIs are generated on board the UAV. The
  use of neural network algorithms allows this process to be implemented in real-time for a wide range of
  observation conditions (different times of day and year). The use of semantic descriptions of the map and
  CI reduces computations compared to traditional pixel-by-pixel matching of raster images. Semantic descriptions
  are compared by matching object classes, their attributes, and relationships. The work presents
  a general algorithm for visual navigation, the main stages of the methodology for forming semantic descriptions,
  and the algorithm for comparing and identifying semantic descriptions of CIs and map descriptions.
  A hierarchical algorithm for comparing and identifying images based on the sequential application
  of semantic and raster descriptions of observed scenes is proposed. It is shown that the use of the procedure
  for comparing semantic descriptions of CIs and maps by the classes of objects present significantly
  reduces the computations necessary for image identification

• ORGANIZATION OF MOBILE ROBOTS NAVIGATION BASED ON COGNITIVE MAPPING

  А.М. Korsakov , V. V. Ivanova

  2026-04-29

  Abstract ▼

  The article addresses the relevant task of ensuring the autonomy of mobile robots in complex conditions, where the use of traditional navigation methods based on global coordinate systems and satellite data is impossible or ineffective. To solve this problem, an approach based on cognitive (interpretive) navigation is proposed, where semantic understanding of the environment plays the central role. The key feature of the method is the construction of a cognitive map – a semantically oriented graph whose vertices correspond to landmark objects (or groups of homogeneous landmarks), and whose edges correspond to fixed sets of information-motor actions (elementary conditioned behavioral patterns). Thus, the robot's route while moving along the cognitive map is reduced to a fixed set of information-motor actions. The map construction process is carried out automatically based on a pre-obtained semantically segmented image of the terrain, which allows the mobile robot to acquire a priori information about the relative positions and shapes of the landmarks. To formalize the navigation process and manage the robot's behavior based on the cognitive map, the authors propose a specially developed formal language, LRNB (Language of Robot Navigation Behavior). This language allows the decomposition of complex missions into elementary information-motor actions, the specification of their completion conditions, and the description of interaction scenarios with dynamic and static objects. The work details the principles of building a cognitive map, the syntax of the LRNB language, and the mechanism for forming a route as a sequence of commands. The practical part includes the results of verifying the approach in a simulation environment using a specially developed emulator, as well as preliminary field tests on a laboratory tracked mobile robot, which confirmed the fundamental feasibility of the proposed approach. The obtained results indicate the potential of the method for application in critically important scenarios, such as disaster zones, areas of electronic warfare, and other environments with a high degree of uncertainty. Further work plans are proposed, related to bringing experimental conditions closer to the real-world conditions of potential operation.