Automatic seedling avoidance system for paddy field weeder based on deep learning and adrc control

Abstract

The invention discloses an automatic seedling avoidance system for paddy field weeders based on deep learning and ADRC control, which includes: an image acquisition module M0, a rice seedling detection module M1 based on the SSD algorithm, a seedling line fitting module M2, and a control based on the ADRC algorithm. Module M3; collect rice seedling images through the image acquisition module, input them into the rice seedling detection module M1, perform detection and recognition through the SSD target detection algorithm model, and obtain the recognition results; fit the seedling emergence line according to the recognition results, and use the maximum and minimum spacing optimization Algorithm, the position of the weeding wheel is optimized through the input seedling line information, and the target position y of the weeding wheel is obtained. r ;With target position y r In order to achieve the control goal, the ADRC controller is used to realize the automatic interference rejection control of the weeding process to minimize the seedling damage rate; and without adding sensors, it can improve the control accuracy and reduce the manufacturing cost of the weeding machine; it can also solve the complex operating environment of rice fields. The key technical issues of intelligent, efficient and low-loss mechanical weeding.

Description

technical field [0001] The invention relates to the technical field of measuring devices, in particular to a light-sensitive intelligent body-shaped dimension ruler. Background technique [0002] In farmland ecosystems, weeds are one of the main reasons for the decline in crop yield and quality, so the task of weeding becomes particularly important. There are two main methods of weeding in farmland: chemical weeding and mechanical weeding. For chemical weeding, the application of chemical herbicides is a simple and efficient way to control weeds in paddy fields, but the extensive application of herbicides has also brought many negative problems such as crop phytotoxicity, weed resistance and environmental pollution. As an environmentally friendly and green weeding method, mechanical weeding is in line with the development direction of the agricultural industry proposed by the state to promote agriculture with quality and green. [0003] At present, the research on farmland...

AI Technical Summary

Problems solved by technology

[0005] In view of this, the present invention provides an automatic seedling avoidance method for paddy field weeders based on deep learning and ADRC control, and comprehensively uses theories and methods such as deep learning, target detection, and automatic control to solve the problem of intelligent, high-efficiency, and low-loss problems in the complex operating environment of paddy fields. Key Technical Problems of Mechanical Weeding

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