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LiDAR-Only Crop Navigation for Symmetrical Robot

This paper presents a navigation approach for autonomous agricultural robots based on LiDAR data. This navigation approach is divided into two parts: a line finding algorithm and a control algorithm. The paper proposes several line finding algorithms (based on PEARL/Ruby approach) that extract lines...

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Detalles Bibliográficos
Autores principales: Guyonneau, Rémy, Mercier, Franck, Oliveira, Gabriel Freitas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694536/
https://www.ncbi.nlm.nih.gov/pubmed/36433514
http://dx.doi.org/10.3390/s22228918
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author Guyonneau, Rémy
Mercier, Franck
Oliveira, Gabriel Freitas
author_facet Guyonneau, Rémy
Mercier, Franck
Oliveira, Gabriel Freitas
author_sort Guyonneau, Rémy
collection PubMed
description This paper presents a navigation approach for autonomous agricultural robots based on LiDAR data. This navigation approach is divided into two parts: a line finding algorithm and a control algorithm. The paper proposes several line finding algorithms (based on PEARL/Ruby approach) that extract lines from a LiDAR data set. Once the lines have been processed from the data set, a control algorithm filters these lines and, using a fuzzy controller, generates the wheel speed commands to move the robot among the crop rows. This navigation approach was tested using a simulator built on ROS middle-ware and Gazebo (the source codes of the simulation are available on GitHub). The results of the simulated experiments show that the proposed approach performs well for a large range of crop configurations (with or without considering weeds, with or without holes in the crop rows…).
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spelling pubmed-96945362022-11-26 LiDAR-Only Crop Navigation for Symmetrical Robot Guyonneau, Rémy Mercier, Franck Oliveira, Gabriel Freitas Sensors (Basel) Article This paper presents a navigation approach for autonomous agricultural robots based on LiDAR data. This navigation approach is divided into two parts: a line finding algorithm and a control algorithm. The paper proposes several line finding algorithms (based on PEARL/Ruby approach) that extract lines from a LiDAR data set. Once the lines have been processed from the data set, a control algorithm filters these lines and, using a fuzzy controller, generates the wheel speed commands to move the robot among the crop rows. This navigation approach was tested using a simulator built on ROS middle-ware and Gazebo (the source codes of the simulation are available on GitHub). The results of the simulated experiments show that the proposed approach performs well for a large range of crop configurations (with or without considering weeds, with or without holes in the crop rows…). MDPI 2022-11-18 /pmc/articles/PMC9694536/ /pubmed/36433514 http://dx.doi.org/10.3390/s22228918 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Guyonneau, Rémy
Mercier, Franck
Oliveira, Gabriel Freitas
LiDAR-Only Crop Navigation for Symmetrical Robot
title LiDAR-Only Crop Navigation for Symmetrical Robot
title_full LiDAR-Only Crop Navigation for Symmetrical Robot
title_fullStr LiDAR-Only Crop Navigation for Symmetrical Robot
title_full_unstemmed LiDAR-Only Crop Navigation for Symmetrical Robot
title_short LiDAR-Only Crop Navigation for Symmetrical Robot
title_sort lidar-only crop navigation for symmetrical robot
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694536/
https://www.ncbi.nlm.nih.gov/pubmed/36433514
http://dx.doi.org/10.3390/s22228918
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AT oliveiragabrielfreitas lidaronlycropnavigationforsymmetricalrobot