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• HYBRID METHOD OF ROUTE CONFIGURATION PLANNING ON A TERRAIN MAP UNDER CONDITIONS OF PARTIAL UNCERTAINTY

  М. I. Beskhmelnov, B.К. Lebedev, О.B. Lebedev

  2025-04-27

  Abstract ▼

  The paper describes a hybrid algorithm for situational trajectory planning under partial uncertainty for a
  two-dimensional space based on the integration of the wave and ant algorithms, which allows constructing trajectories
  of minimum length in real time with simultaneous optimization of a number of other quality criteria for
  the constructed path. The processes of forming a trajectory section and moving an object along it alternate at
  each step. The trajectory is formed sequentially (step by step) at two levels of each step. The local visibility zone
  and the region covered by it on the terrain map are formed and oriented relative to the current reference vector.
  The first-level procedures sequentially form a chain of pairwise adjacent regions with localized obstacles on the
  terrain map in steps. The second-level procedures form a set of trajectories for the passage of a moving object
  through a region at a step. When the chain of regions merges, a terrain region is formed through which the trajectory
  is laid. The entire trajectory is a set of individual trajectories for the passage of a moving object through
  regions connecting its initial position with the target position. The search for a solution is carried out by a population
  of agents on a solution search graph. The vertices of the set correspond to the cells of the region. Two
  vertices are connected by an edge if the corresponding cells on the terrain model in the form of a discrete working
  field are adjacent and the transition of the connection from one cell to another is possible. It should be noted
  that the synthesis of the trajectory and the movement of a moving object under uncertainty is a complex task that
  requires the integration of various sensor systems, data processing algorithms, path planning algorithms and
  motion control systems. The constant development of technologies in the fields of artificial intelligence, machine
  vision and robotics allows the creation of increasingly sophisticated autonomous navigation systems. However,
  complete autonomy and guaranteed safety of a moving object under any conditions still remain complex tasks
  for research.

• BIOINSPIRED SEARCH IN THE COMPLETE GRAPH OF A PERFECT MATCH OF MAXIMUM POWER

  B. К. Lebedev, О.B. Lebedev, М. А. Ganzhur, М. I. Beskhmelnov

  2025-01-30

  Abstract ▼

  A reconfigurable architecture of a hybrid multi-agent decision-making system based on swarm algorithm
  paradigms has been developed. The reconfigurable architecture allows implementing the following
  hybridization methods by tuning: high-level and low-level hybridization by nesting, preprocessor/
  postprocessor type, co-algorithmic based on one or several types of algorithms. A methodology for
  synthesizing a perfect matching of minimum weight in a complete graph based on the basic principles of
  hybridization of search. evolutionary procedures has been proposed. In this paper, the swarm agents are
  transforming chromosomes, which are the genotypes of the solution. An ordered list of the set of graph
  vertices is used as the solution code. A structure of an ordered matching code has been developed, the
  main advantage of which is that one solution (matching) corresponds to one code and vice versa. The
  properties of the ordered code have been determined and encoding and decoding algorithms have been
  developed. The hybrid system operation starts with the random generation by a swarm of bees of an arbitrary
  set of solutions differing from each other in the form of an initial set of chromosomes. The key operation
  of the bee algorithm is the study of promising solutions and their neighborhoods in the search space.
  A method for forming neighborhoods of solutions with an adjustable degree of similarity and closeness
  between them has been developed. At subsequent stages of the multi-agent system operation, solutions are
  searched for by procedures built on the basis of hybridization of the swarm and ant algorithms. A distinctive
  feature of hybridization is the preservation of the autonomy of the hybridized algorithms. Note that a
  single data structure is used to represent solutions in the algorithms, which simplifies the docking of the
  developed procedures. An approach to constructing a modified paradigm of a swarm of transforming
  chromosomes is proposed. The search for solutions is performed in an affine space. In the process of
  searching, permanent transformations (transitions) of chromosomes into states with the best value of the
  objective function of the solution (gradient strategy) are carried out. The process of finding solutions is
  iterative. At each iteration, the chromosomes are transformed (transitioned) into states with better values
  of the objective function of the solution. The purpose of transforming a chromosome that tends to be the
  best chromosome into a new state is to minimize the degree of difference by changing the mutual arrangement
  of elements in an ordered list, which corresponds to an increase in the weight of the affine
  connection. The chromosomes updated after the transformation are, in turn, the base points in subsequent
  transformations. As a result of the experiments, it was found that the quality indicators of the developed
  algorithms have higher values than in the works presented in the literature.

• DECENTRALIZED CONTROL OF A GROUP OF AUTONOMOUS MOBILE OBJECTS WHEN FORMING A TRAJECTORY OF MOVEMENT

  B.К. Lebedev, О.B. Lebedev, М. I. Beskhmelnov

  2025-01-14

  Abstract ▼

  The article considers algorithms for generating unmanned aerial vehicles motion trajectories during
  search and rescue and liquidation operations. The methods and algorithms for controlling the motion of a
  unmanned aerial vehicles group in formation, when deployed in a line, when deployed in a rank, when
  turning, in a column are described. Control is carried out using alternative collective adaptation algorithms
  based on the ideas of collective behavior. The operating principles of one adaptation machine are
  considered. The purpose of controlling slave robots is to minimize deviations. To implement the adaptation
  mechanism, the parameters of the vector are matched with adaptation machines that model the behavior
  of adaptation objects in the environment. A structure has been developed for the process of alternative
  collective adaptation of parameters that control the motion of a group of unmanned aerial vehicles in
  formation. Original rules for controlling parameters have been developed that have a number of advantages
  over other methods: complete decentralization of control in combination with dynamic correction
  of robot parameters that set the position and orientation of the robot in an absolute coordinate system,
  and the linear velocity of the robot, respectively. A structure of a maneuver performed by a robot to correct
  parameter deviations is proposed. Control is performed using an alternative collective adaptation algorithm
  based on the ideas of collective behavior of adaptation objects, which allows for efficient processing
  of emergency situations, such as agent failure, changes in the number of agents due to failure or sudden
  acquisition of communication with the next agent, as well as in conditions of measurement errors and
  noise that satisfy certain restrictions.