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The development of the agricultural industry is impossible without automation of the processes of field preparation and harvesting. One of the ways to solve this problem is the implementation of machine vision technologies supplemented with neural networks in the implementation of automated control systems for agricultural equipment. The implementation of machine vision algorithms will allow the recognition of objects in the workspace, the adjustment of the route of movement of technology, the realization of its various operating scenarios. Neural networks will allow you to analyze the surrounding objects and choose the best route to move. In this article, we consider an algorithm for determining objects based on machine vision technologies and the selection of a working area on a frame. The analysis of the intersection of the working area with recognized objects allows you to create controls that regulate the trajectory of traffic. The obtained results are experimentally verified on a laboratory prototype of a universal platform for agricultural machinery. Various approaches to the selection of object boundaries are considered and tested.

The control system of universal platform for agriculture based on machine vision technology