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• STUDY OF PATH PLANNING METHODS IN TWO-DIMENSIONAL MAPPED ENVIRONMENTS

  М. Y. Medvedev, V.K. Pshikhopov, D.О. Brosalin, B.V. Gurenko, М.А. Vasileva, Hamdan Nizar

  2022-08-09

  Abstract ▼

  The article studies the problem of motion planning in two-dimensional mapped environments.
  The review and analysis of known planning algorithms based on Voronoi diagrams, probabilistic
  road maps, rapidly growing random trees, Dijkstra algorithms, A*, D* and their modifications, artificial
  potential fields and intelligent heuristics are carried out. Based on the analysis, it is concluded
  that classical methods in dynamic environments require significant costs in terms of calculation time
  and the amount of memory used. The conclusion is made about the relevance of the development of
  algorithms that increase the efficiency of known planning methods. In this regard, this article is devoted
  to the development of a modified algorithm of rapidly growing random trees and the study of its
  effectiveness in comparison with known methods. The article presents a modified algorithm for rapidly
  growing random trees, characterized in that when checking for a path to a new potential node of
  the tree, the path to some area near the specified node is checked. This reduces the number of nodes
  in the tree under construction. The developed algorithm is first compared with the traditional algorithm
  of fast-growing random trees. The comparison is made by the trajectory calculation time, the
  amount of memory required, the path length and the percentage of situations in which the trajectory
  to the target point was successfully found. Next, the developed algorithm is compared with the planning
  algorithms of other classes. The study uses representative samples of numerical experiments and
  various environments that differ in the density of obstacles and the presence of mazes. A study of
  planning algorithms using the results of experiments on a ground-based wheeled robot is also being
  conducted. Based on the results of numerical and real experiments, conclusions are drawn about the
  advantages and disadvantages of the developed algorithm of motion planning and the feasibility of its
  application in various environments.

• INTEGRATION OF LOCAL AND GLOBAL SCHEDULER INTO A MOBILE ROBOT CONTROL SYSTEM

  D.O. Brosalin, B.V. Gurenko, М. Y. Medvedev

  2024-01-05

  Abstract ▼

  This paper investigates the problem of integrating local and global motion planning methods
  in a robot control system. The current level of technological development allows mobile robots
  not only to follow predetermined coordinates, but also to make real-time decisions independently
  of the operator, reacting to changes in the environment. However, the dynamic nature of the environment and the constraints on planning time, as well as the high speeds of mobile robots, complicate
  the problems solved by planning algorithms. In this paper, some motion planning methods
  based on cellular decomposition (such as A*, D* and Wavefront) and random search procedures
  on graphs (such as fast growing random RRT trees and probabilistic roadmaps PRM) integrated
  with a motion trajectory prediction algorithm (DWA) are reviewed. A study of the performance
  characteristics of each of the above algorithms has been conducted, as well as a series of numerical
  and in-situ experiments to analyze the effect of map topology on the execution time and
  memory usage of the algorithms. The effect of the speed of local and global planning under different
  configurations of the external environment was investigated. To confirm the effectiveness of the
  investigated algorithms in real conditions, software for a mobile robot based on a wheeled chassis
  has been created. The paper presents structural and functional schemes of interaction between the
  implemented modules of planning and motion control of the mobile robot and the environment.
  It also presents a mathematical model of a wheeled platform, for which, based on the considered
  methods, motion planning algorithms are developed. In this paper, quantitative measures including
  the computation time of the motion planning algorithm and the amount of memory used by the
  algorithms under different environment maps are evaluated. Both environments with randomly
  placed obstacles and different types of mazes are considered. The implementation of the developed
  algorithms in the ROS-2 environment is also described. It is shown that the implemented system
  provides real-time control and motion planning of the mobile robot.