Unmanned Ground Vehicle for Identifying Trees Infested with Bark Beetles

This research presents an unmanned ground vehicle for identifying infested trees by bark beetles in mountain forests. The ground vehicle uses sensors for autonomous navigation and obstacle avoidance. The identification of infested trees is carried out by classifying the resin stains on the bark of u...

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Main Authors: Jonathan Flores, Sergio Salazar, Iván González-Hernández, Yukio Rosales-Luengas, Rogelio Lozano
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Machines
Subjects:
Online Access:https://www.mdpi.com/2075-1702/12/12/944
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author Jonathan Flores
Sergio Salazar
Iván González-Hernández
Yukio Rosales-Luengas
Rogelio Lozano
author_facet Jonathan Flores
Sergio Salazar
Iván González-Hernández
Yukio Rosales-Luengas
Rogelio Lozano
author_sort Jonathan Flores
collection DOAJ
description This research presents an unmanned ground vehicle for identifying infested trees by bark beetles in mountain forests. The ground vehicle uses sensors for autonomous navigation and obstacle avoidance. The identification of infested trees is carried out by classifying the resin stains on the bark of unhealthy trees with a computer vision algorithm. This approach proposes tracking bark beetle spread in forest trees with image data of the infested trees considering resin sprouts as early indicators of the infestation in contrast to aerial monitoring, which only detects trees in advanced stages. Terrain autonomous vehicle direction is controlled by changing the velocities of left- and right-side wheels. A rotating LiDAR sensor is used to detect trees and avoid objects. The dynamic model of the vehicle is presented, and a control algorithm is proposed for path-following. Moreover, the stability of the system is proven using a Lyapunov function. In order to demonstrate the performance of the control and classification algorithms, experimental results from an outdoor forest environment are presented.
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institution Kabale University
issn 2075-1702
language English
publishDate 2024-12-01
publisher MDPI AG
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series Machines
spelling doaj-art-ec8a1766099b4240aa5c4b76665ee6c12024-12-27T14:37:15ZengMDPI AGMachines2075-17022024-12-01121294410.3390/machines12120944Unmanned Ground Vehicle for Identifying Trees Infested with Bark BeetlesJonathan Flores0Sergio Salazar1Iván González-Hernández2Yukio Rosales-Luengas3Rogelio Lozano4Program of Aerial and Submarine Autonomous Navigation Systems, Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, MexicoProgram of Aerial and Submarine Autonomous Navigation Systems, Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, MexicoProgram of Aerial and Submarine Autonomous Navigation Systems, Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, MexicoProgram of Aerial and Submarine Autonomous Navigation Systems, Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, MexicoProgram of Aerial and Submarine Autonomous Navigation Systems, Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, MexicoThis research presents an unmanned ground vehicle for identifying infested trees by bark beetles in mountain forests. The ground vehicle uses sensors for autonomous navigation and obstacle avoidance. The identification of infested trees is carried out by classifying the resin stains on the bark of unhealthy trees with a computer vision algorithm. This approach proposes tracking bark beetle spread in forest trees with image data of the infested trees considering resin sprouts as early indicators of the infestation in contrast to aerial monitoring, which only detects trees in advanced stages. Terrain autonomous vehicle direction is controlled by changing the velocities of left- and right-side wheels. A rotating LiDAR sensor is used to detect trees and avoid objects. The dynamic model of the vehicle is presented, and a control algorithm is proposed for path-following. Moreover, the stability of the system is proven using a Lyapunov function. In order to demonstrate the performance of the control and classification algorithms, experimental results from an outdoor forest environment are presented.https://www.mdpi.com/2075-1702/12/12/944UGVtree classificationbark beetle identification
spellingShingle Jonathan Flores
Sergio Salazar
Iván González-Hernández
Yukio Rosales-Luengas
Rogelio Lozano
Unmanned Ground Vehicle for Identifying Trees Infested with Bark Beetles
Machines
UGV
tree classification
bark beetle identification
title Unmanned Ground Vehicle for Identifying Trees Infested with Bark Beetles
title_full Unmanned Ground Vehicle for Identifying Trees Infested with Bark Beetles
title_fullStr Unmanned Ground Vehicle for Identifying Trees Infested with Bark Beetles
title_full_unstemmed Unmanned Ground Vehicle for Identifying Trees Infested with Bark Beetles
title_short Unmanned Ground Vehicle for Identifying Trees Infested with Bark Beetles
title_sort unmanned ground vehicle for identifying trees infested with bark beetles
topic UGV
tree classification
bark beetle identification
url https://www.mdpi.com/2075-1702/12/12/944
work_keys_str_mv AT jonathanflores unmannedgroundvehicleforidentifyingtreesinfestedwithbarkbeetles
AT sergiosalazar unmannedgroundvehicleforidentifyingtreesinfestedwithbarkbeetles
AT ivangonzalezhernandez unmannedgroundvehicleforidentifyingtreesinfestedwithbarkbeetles
AT yukiorosalesluengas unmannedgroundvehicleforidentifyingtreesinfestedwithbarkbeetles
AT rogeliolozano unmannedgroundvehicleforidentifyingtreesinfestedwithbarkbeetles