Computer Vision Direction System

Abstract

One of the most relevant areas of development of artificial intelligence in recent years has become computer vision. The ability to see is the most important property of a person. It is with the help of vision that we receive the greatest amount of information about the world around us.

Thanks to the accumulated experience and knowledge, we easily recognize objects and distinguish them from each other, navigate in space. Over time, the idea arose to endow artificial intelligence with vision. However, despite the fact that modern computers have long surpassed humans in the field of computing and information processing, image analysis was rather important task for them.

Many things that only a few decades ago could only be found in science fiction literature have become an integral part of our lives today. For a modern person, there is nothing surprising in the fact, that robots work instead of workers in advanced automated factories, driverless cars drive on city roads, and artificial neural networks create masterpieces that are not inferior to the works of professional artists. 

The areas of application of computer vision are quite extensive: from industrial means of monitoring technical processes to autonomous control systems that make decisions based on the analysis of the received video information.

One of the most promising areas is the use of computer vision systems in automated logistics systems.

A striking example of this is the widespread use of transport robots by large modern companies, which ensure the movement of goods in an industrial environment without the participation of an operator. These machines are used in enterprises to transport raw materials — from warehouse to workshop, blanks — between production stages, finished products from production to warehouse and from warehouse to shipment. The use of such vehicles allows you to reduce transportation costs associated with the human factor and loss of time, increase safety at the enterprise, and speed up production processes.