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Design and development of orchard autonomous navigation spray system

Driven by the demand for efficient plant protection in orchards, the autonomous navigation system for orchards is hereby designed and developed in this study. According to the three modules of unmanned system “perception-decision-control,” the environment perception and map construction strategy bas...

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Autores principales: Wang, Shubo, Song, Jianli, Qi, Peng, Yuan, Changjian, Wu, Hecheng, Zhang, Lanting, Liu, Weihong, Liu, Yajia, He, Xiongkui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9376256/
https://www.ncbi.nlm.nih.gov/pubmed/35979071
http://dx.doi.org/10.3389/fpls.2022.960686
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author Wang, Shubo
Song, Jianli
Qi, Peng
Yuan, Changjian
Wu, Hecheng
Zhang, Lanting
Liu, Weihong
Liu, Yajia
He, Xiongkui
author_facet Wang, Shubo
Song, Jianli
Qi, Peng
Yuan, Changjian
Wu, Hecheng
Zhang, Lanting
Liu, Weihong
Liu, Yajia
He, Xiongkui
author_sort Wang, Shubo
collection PubMed
description Driven by the demand for efficient plant protection in orchards, the autonomous navigation system for orchards is hereby designed and developed in this study. According to the three modules of unmanned system “perception-decision-control,” the environment perception and map construction strategy based on 3D lidar is constructed for the complex environment in orchards. At the same time, millimeter-wave radar is further selected for multi-source information fusion for the perception of obstacles. The extraction of orchard navigation lines is achieved by formulating a four-step extraction strategy according to the obtained lidar data. Finally, aiming at the control problem of plant protection machine, the ADRC control strategy is adopted to enhance the noise immunity of the system. Different working conditions are designed in the experimental section for testing the obstacle avoidance performance and navigation accuracy of the autonomous navigation sprayer. The experimental results show that the unmanned vehicle can identify the obstacle quickly and make an emergency stop and find a rather narrow feasible area when a moving person or a different thin column is used as an obstacle. Many experiments have shown a safe distance for obstacle avoidance about 0.5 m, which meets the obstacle avoidance requirements. In the navigation accuracy experiment, the average navigation error in both experiments is within 15 cm, satisfying the requirements for orchard spray operation. A set of spray test experiments are designed in the final experimental part to further verify the feasibility of the system developed by the institute, and the coverage rate of the leaves of the canopy is about 50%.
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spelling pubmed-93762562022-08-16 Design and development of orchard autonomous navigation spray system Wang, Shubo Song, Jianli Qi, Peng Yuan, Changjian Wu, Hecheng Zhang, Lanting Liu, Weihong Liu, Yajia He, Xiongkui Front Plant Sci Plant Science Driven by the demand for efficient plant protection in orchards, the autonomous navigation system for orchards is hereby designed and developed in this study. According to the three modules of unmanned system “perception-decision-control,” the environment perception and map construction strategy based on 3D lidar is constructed for the complex environment in orchards. At the same time, millimeter-wave radar is further selected for multi-source information fusion for the perception of obstacles. The extraction of orchard navigation lines is achieved by formulating a four-step extraction strategy according to the obtained lidar data. Finally, aiming at the control problem of plant protection machine, the ADRC control strategy is adopted to enhance the noise immunity of the system. Different working conditions are designed in the experimental section for testing the obstacle avoidance performance and navigation accuracy of the autonomous navigation sprayer. The experimental results show that the unmanned vehicle can identify the obstacle quickly and make an emergency stop and find a rather narrow feasible area when a moving person or a different thin column is used as an obstacle. Many experiments have shown a safe distance for obstacle avoidance about 0.5 m, which meets the obstacle avoidance requirements. In the navigation accuracy experiment, the average navigation error in both experiments is within 15 cm, satisfying the requirements for orchard spray operation. A set of spray test experiments are designed in the final experimental part to further verify the feasibility of the system developed by the institute, and the coverage rate of the leaves of the canopy is about 50%. Frontiers Media S.A. 2022-08-01 /pmc/articles/PMC9376256/ /pubmed/35979071 http://dx.doi.org/10.3389/fpls.2022.960686 Text en Copyright © 2022 Wang, Song, Qi, Yuan, Wu, Zhang, Liu, Liu and He. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Wang, Shubo
Song, Jianli
Qi, Peng
Yuan, Changjian
Wu, Hecheng
Zhang, Lanting
Liu, Weihong
Liu, Yajia
He, Xiongkui
Design and development of orchard autonomous navigation spray system
title Design and development of orchard autonomous navigation spray system
title_full Design and development of orchard autonomous navigation spray system
title_fullStr Design and development of orchard autonomous navigation spray system
title_full_unstemmed Design and development of orchard autonomous navigation spray system
title_short Design and development of orchard autonomous navigation spray system
title_sort design and development of orchard autonomous navigation spray system
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9376256/
https://www.ncbi.nlm.nih.gov/pubmed/35979071
http://dx.doi.org/10.3389/fpls.2022.960686
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