A control algorithm for autonomous objects in complex, hard-to-predict industrial timber harvesting conditions
Abstract
A control algorithm for autonomous objects in complex, hard-to-predict industrial timber harvesting conditions
Incoming article date: 09.03.2023The article outlines the features of the developed algorithm for controlling autonomous industrial forest management facilities under real operating conditions under the forest canopy. A significant challenge faced by the developers in the presented algorithm was the practical absence of global navigation in the areas of use of potential autonomous industrial forest management objects. Thus the only alternative was local positioning algorithms, which of the existing ones were also unserviceable under real forest canopy conditions. The problem was exacerbated by the high requirements for positioning accuracy not so much for autonomous objects as for positioning accuracy relative to the object of work of the contact elements of technological equipment directly implementing the operations of the industrial timber harvesting process. The developed concept of local positioning has no analogues in the world, belongs to the algorithms of the latest generation, created by the authors on the basis of mathematical modelling of the operations of industrial forestry process and implemented in registered software complexes to manage the information flows that ensure the sustainable functioning of autonomous objects of industrial forestry in real operating conditions.
Keywords: algorithm, method, synthesis, positioning technology, control method, digital model, automation, digitalisation, modelling