Abstract
The Navigation System discussed in the paper can recognize ripe fruit automatically for agricultural harvesting machinery by machine vision technology, and then achieve the purpose of autonomous positioning and navigation through autonomous path planning. In order to achieve this process, agricultural machinery positioning and navigation system must have high precision and fast image processing algorithm. Based on this, this paper introduces the extreme learning machine algorithm into the agricultural machinery navigation system, combined with BP neural network algorithm, through the determination of the image coordinates of ripe fruit and fruit tree, to achieve the rapid navigation of agricultural machinery operation. In order to verify the feasibility of the scheme, the computational efficiency and precision of the algorithm are counted. The experimental results show that the picking efficiency has been improved obviously and the picking accuracy has been improved by using the extreme learning machine, which can meet the design requirements of modern agricultural machinery and equipment.
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