IMPROVEMENT OF ROBOTIC SYSTEMS BASED ON VISUAL CONTROL - Ігор Шакирович Невлюдов; Олександр Михайлович Цимбал; Артем Ігорович Бронніков (Сучасний стан наукових досліджень та технологій в промисловості)
The subject of research in the article is the use of adaptive visual control in flexible integrated robotic systems. The goal of the work is the integration of visual control facilities into automated control systems for transport and handling operations of flexible integrated production. The article solves the following tasks: analyze the application of visual control methods in robotics, consider methods for improving adaptive visual work control systems, formulate the basic requirements for adaptive visual control systems, and develop a control model for a mobile robot in the space of a flexible integrated production systems and computer vision systems. To solve the set tasks, the methods of set theory, methods of automatic control theory, and methods of the theory of image processing were used. The following results were obtained: the analysis of visual control systems was carried out from the point of view of solving the problems of flexible integrated systems of modern production; the adaptive visual control scheme was improved by introducing a declarative workspace model and a functional model of a flexible integrated system; the main requirements and tasks of adaptive visual control systems are formulated; considered the main stages of processing visual information and their practical implementation, including multi-zone workspaces; a model of visual control of a mobile robot in a flexible integrated production workspace has been developed; the practical tasks of managing mobile platforms have been solved. Conclusions: the use of adaptive visual control in a production environment will allow combining the elements of flexible integrated production distributed in space, providing monitoring, control and refinement of control processes in real time, the functioning of intelligent control tools, which will improve the quality of control processes.