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In Field of agriculture, the cultural manual inspection remains as a slow and tedious work along with the high error factor, in order to overcome this problem, this research work illustrates the different techniques used to initiate automated robots to perform the agricultural task. Intelligent system is required for cultivation, and harvesting of crops, which can identify the crops according to its features, margin, and colour. As the need of agriculture is Automation, Information technology and robotics for harvesting. This paper is the study of various technologies of robotics for cultivation. This paper shows how different robots work in the field of agriculture for capturing the fruits, cultivation of cotton, identification of weed and crops etc. by using the Machine learning, Convolutional Neural network(CNN), and multilayer preceptor. Further the study shows that the fruit detection was done by trained algorithm of image processing with extraction of only the required features. The colour, shape, margin, texture was provided as the input test image .The main goal of this paper is to develop an automated fruit recognition and picker system using the laser sensor and machine vision that remains similar to that of human picker. In the field of agriculture, the cultural manual inspection remains as a slow and tedious work along with high error factor. To overcome this problem this paper shows the different techniques used to make the automated robots to perform the agricultural task. The intelligent system is required for cultivation, and harvesting of crops in order to identify the crops according to its features, margin, and colour. |
