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Precision route planning method based on UAV remote sensing and genetic algorithm for weeding machine

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Abstract

Weeds are one of the most important agricultural hazards. The widespread spraying of herbicides not only wastes chemicals but also pollutes the environment. In this paper, a precisely route planning method for weeding machine based on UAV(Unmanned Aerial Vehicle) images was proposed. A genetic algorithm (GA) was used to optimize the operation route. For genetic algorithm, a new route encoding approach and fitness function were presented. The GA-optimized operating route saves up to 80.03% of working time compared to uniform spraying in the experiment. This method could effectively plan the operation route of spraying machines and reduce herbicide usage. This was important for both cost-saving and environment protection.

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Acknowledgements

This research was funded by National Key Research and Development Project (2019YFB1312303).

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Authors and Affiliations

  1. College of Engineering, China Agricultural University, Qinghua Rd.(E) No.17, Haidian District, Beijing, 100083, People’s Republic of China

    Kunlin Zou, Han Wang, Fan Zhang, Chunlong Zhang & Deng Kai

  2. Zhejiang Lab, Kechuang Avenue, Zhongtai Street, Hangzhou, 310000, People’s Republic of China

    Chunlong Zhang

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  1. Kunlin Zou
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  2. Han Wang
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  3. Fan Zhang
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  4. Chunlong Zhang
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Correspondence to Chunlong Zhang.

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Zou, K., Wang, H., Zhang, F. et al. Precision route planning method based on UAV remote sensing and genetic algorithm for weeding machine. Appl Intell 53, 11203–11213 (2023). https://doi.org/10.1007/s10489-022-03965-8

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