Research of models and methods for routing and practical implementation of autonomous movement by unmanned transport systems for cargo delivery

Abstract

Modern challenges in the field of transport logistics associated with the need to increase the speed of cargo transportation and reduce the cost of transportation require the development of solutions that will allow the introduction of unmanned vehicles to solve logistics problems. Within the framework of this paper, a new problem of routing an unmanned transport system through delivery points using annealing simulation methods and an ant colony algorithm is considered. These methods are chosen taking into account the real situation of complication of the conditions of possible delivery, the emergence of closed areas for delivery, obtaining a large number of points for delivery, or the emergence of other features. The selected algorithms are relatively simple to implement and, at the same time, form acceptable routes of movement, taking into account the initial data. These algorithms are studied in the software simulation environment Gazebo for the possibility of their application in unmanned transport systems and their effectiveness in constructing alternative traffic routes. In the software simulation, a program code for the autonomous movement of an unmanned vehicle is developed and a simulation environment is formed taking into account the test data. In the test environment, the results of the ant colony algorithm are checked against the test data, and special attention is paid to the study of the speed and accuracy of the selected algorithms. It is worth noting that the annealing simulation algorithm allows you to quickly optimize a given route, however, to obtain more accurate results, you should additionally use other optimization methods, such as the ant colony algorithm. As a result of the proposed methods application, it is concluded that it is possible to form the optimal route of movement relative to the initial data within the length of the path and the speed of the generated route.