АЛГОРИТМ МНОГОКРИТЕРИАЛЬНОГО ПОИСКА ТРАЕКТОРИИ ДВИЖЕНИЯ РОБОТА НА МНОГОСЛОЙНОЙ КАРТЕ

Abstract

Introduction: A complex environment is characterized by the possibility to decompose the factors affecting the robot into independent layers. As the robot is moving in a complex environment, it is exposed to negative factors which affect its ability to achieve the goal. The problem arises how to choose the motion trajectory while minimizing the negative effects on the robot and the distance covered. Purpose: Developing and analyzing an algorithm for two-criteria optimization of robot motion trajectory, taking into account the desired criteria about the interaction with the environment and the trajectory length. Results: We have developed and implemented an algorithm for shortest path search on a map each layer of which displays a property of the space and allows you to take into account the interaction between the robot and the environment, as well as the distance covered. The algorithm implementation is incorporated into the robot group control model. To analyze the algorithm, test multilayer maps were used, with the addition of Gaussian noise. The simulation results are a set of trajectories reflecting the coefficients with which the space properties affect the robot when the initial and final positions on the map are given. A space of the robot motion states demonstrates how the influence of the environment properties on the robot depends on the trajectory length and on the failure risk throughout the path. Practical relevance: The developed algorithm can be applied in planning systems of individual or group motion of robots. The resulting state space reflects the ranges of effective characteristics of the robot when performing tasks in a given environment. As the next step, the developed algorithm will be applied to plan paths on multiscale maps, and sets of trajectories will be built in the state space of a group of robots.