Loading…

A Pesticide Spraying Mission Allocation and Path Planning With Multicopters

This article presents a mission allocation and path-planning solution for the pesticide spraying mission of dense trees in hilly terrains using cooperative multicopters. The problem is formulated as a single-depot single-end multiple traveling salesman problem (mTSP). Three different algorithms, nam...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2024-04, Vol.60 (2), p.2277-2291
Main Authors: Huang, Jing, Du, Baihui, Zhang, Youmin, Quan, Quan, Wang, Ban, Mu, Lingxia
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c246t-a3de1970ae7658965c240d53d9667ba45e73fa19c76c496029bf86fa6356b3643
container_end_page 2291
container_issue 2
container_start_page 2277
container_title IEEE transactions on aerospace and electronic systems
container_volume 60
creator Huang, Jing
Du, Baihui
Zhang, Youmin
Quan, Quan
Wang, Ban
Mu, Lingxia
description This article presents a mission allocation and path-planning solution for the pesticide spraying mission of dense trees in hilly terrains using cooperative multicopters. The problem is formulated as a single-depot single-end multiple traveling salesman problem (mTSP). Three different algorithms, namely classical mTSP algorithm, Grouping-TSP combined algorithm, and Grouping-TSP decoupled algorithm, are developed to solve the proposed mTSP. Simulation results indicate that the classical mTSP algorithm provides an evenly distributed task allocation while the Grouping-TSP combined algorithm delivers the optimal solution. In addition, the Grouping-TSP decoupled algorithm minimizes computational complexity. Both Grouping-TSP algorithms integrate a subregions segmentation process to guarantee collision avoidance between the multicopters.
doi_str_mv 10.1109/TAES.2024.3355028
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3037645855</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10400918</ieee_id><sourcerecordid>3037645855</sourcerecordid><originalsourceid>FETCH-LOGICAL-c246t-a3de1970ae7658965c240d53d9667ba45e73fa19c76c496029bf86fa6356b3643</originalsourceid><addsrcrecordid>eNpNkEtLw0AUhQdRsFZ_gOAi4Dr1Tua9DKVWscVCKy6HaTLRKTGJM8mi_94J7cLVffCdew8HoXsMM4xBPe3yxXaWQUZnhDAGmbxAE8yYSBUHcokmAFimKmP4Gt2EcIgjlZRM0FuebGzoXeFKm2w7b46u-UrWLgTXNkle121h-rE1TZlsTP-dbGrTNCP06eK0Huoobrve-nCLripTB3t3rlP08bzYzV_S1fvydZ6v0iKjvE8NKS1WAowVnEnFWVxDyUipOBd7Q5kVpDJYFYIXNNrP1L6SvDKcML4nnJIpejzd7Xz7O0T3-tAOvokvNQEiOGWSsUjhE1X4NgRvK91592P8UWPQY2Z6zEyPmelzZlHzcNI4a-0_ngIoLMkfZu9m0g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3037645855</pqid></control><display><type>article</type><title>A Pesticide Spraying Mission Allocation and Path Planning With Multicopters</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Huang, Jing ; Du, Baihui ; Zhang, Youmin ; Quan, Quan ; Wang, Ban ; Mu, Lingxia</creator><creatorcontrib>Huang, Jing ; Du, Baihui ; Zhang, Youmin ; Quan, Quan ; Wang, Ban ; Mu, Lingxia</creatorcontrib><description>This article presents a mission allocation and path-planning solution for the pesticide spraying mission of dense trees in hilly terrains using cooperative multicopters. The problem is formulated as a single-depot single-end multiple traveling salesman problem (mTSP). Three different algorithms, namely classical mTSP algorithm, Grouping-TSP combined algorithm, and Grouping-TSP decoupled algorithm, are developed to solve the proposed mTSP. Simulation results indicate that the classical mTSP algorithm provides an evenly distributed task allocation while the Grouping-TSP combined algorithm delivers the optimal solution. In addition, the Grouping-TSP decoupled algorithm minimizes computational complexity. Both Grouping-TSP algorithms integrate a subregions segmentation process to guarantee collision avoidance between the multicopters.</description><identifier>ISSN: 0018-9251</identifier><identifier>EISSN: 1557-9603</identifier><identifier>DOI: 10.1109/TAES.2024.3355028</identifier><identifier>CODEN: IEARAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Collision avoidance ; Genetic algorithms ; Mission assignment ; multicopters ; multiple traveling salesman problem (mTSP) ; Optimization ; Path planning ; Pesticides ; point cloud ; precision spraying ; Resource management ; Rotary wing aircraft ; Spraying ; Task analysis ; Traveling salesman problem</subject><ispartof>IEEE transactions on aerospace and electronic systems, 2024-04, Vol.60 (2), p.2277-2291</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c246t-a3de1970ae7658965c240d53d9667ba45e73fa19c76c496029bf86fa6356b3643</cites><orcidid>0000-0002-5471-8339 ; 0000-0001-8002-1263 ; 0000-0001-8216-8998 ; 0000-0002-9731-5943 ; 0000-0002-6466-5277</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10400918$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,27900,27901,54770</link.rule.ids></links><search><creatorcontrib>Huang, Jing</creatorcontrib><creatorcontrib>Du, Baihui</creatorcontrib><creatorcontrib>Zhang, Youmin</creatorcontrib><creatorcontrib>Quan, Quan</creatorcontrib><creatorcontrib>Wang, Ban</creatorcontrib><creatorcontrib>Mu, Lingxia</creatorcontrib><title>A Pesticide Spraying Mission Allocation and Path Planning With Multicopters</title><title>IEEE transactions on aerospace and electronic systems</title><addtitle>T-AES</addtitle><description>This article presents a mission allocation and path-planning solution for the pesticide spraying mission of dense trees in hilly terrains using cooperative multicopters. The problem is formulated as a single-depot single-end multiple traveling salesman problem (mTSP). Three different algorithms, namely classical mTSP algorithm, Grouping-TSP combined algorithm, and Grouping-TSP decoupled algorithm, are developed to solve the proposed mTSP. Simulation results indicate that the classical mTSP algorithm provides an evenly distributed task allocation while the Grouping-TSP combined algorithm delivers the optimal solution. In addition, the Grouping-TSP decoupled algorithm minimizes computational complexity. Both Grouping-TSP algorithms integrate a subregions segmentation process to guarantee collision avoidance between the multicopters.</description><subject>Algorithms</subject><subject>Collision avoidance</subject><subject>Genetic algorithms</subject><subject>Mission assignment</subject><subject>multicopters</subject><subject>multiple traveling salesman problem (mTSP)</subject><subject>Optimization</subject><subject>Path planning</subject><subject>Pesticides</subject><subject>point cloud</subject><subject>precision spraying</subject><subject>Resource management</subject><subject>Rotary wing aircraft</subject><subject>Spraying</subject><subject>Task analysis</subject><subject>Traveling salesman problem</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNpNkEtLw0AUhQdRsFZ_gOAi4Dr1Tua9DKVWscVCKy6HaTLRKTGJM8mi_94J7cLVffCdew8HoXsMM4xBPe3yxXaWQUZnhDAGmbxAE8yYSBUHcokmAFimKmP4Gt2EcIgjlZRM0FuebGzoXeFKm2w7b46u-UrWLgTXNkle121h-rE1TZlsTP-dbGrTNCP06eK0Huoobrve-nCLripTB3t3rlP08bzYzV_S1fvydZ6v0iKjvE8NKS1WAowVnEnFWVxDyUipOBd7Q5kVpDJYFYIXNNrP1L6SvDKcML4nnJIpejzd7Xz7O0T3-tAOvokvNQEiOGWSsUjhE1X4NgRvK91592P8UWPQY2Z6zEyPmelzZlHzcNI4a-0_ngIoLMkfZu9m0g</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Huang, Jing</creator><creator>Du, Baihui</creator><creator>Zhang, Youmin</creator><creator>Quan, Quan</creator><creator>Wang, Ban</creator><creator>Mu, Lingxia</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-5471-8339</orcidid><orcidid>https://orcid.org/0000-0001-8002-1263</orcidid><orcidid>https://orcid.org/0000-0001-8216-8998</orcidid><orcidid>https://orcid.org/0000-0002-9731-5943</orcidid><orcidid>https://orcid.org/0000-0002-6466-5277</orcidid></search><sort><creationdate>20240401</creationdate><title>A Pesticide Spraying Mission Allocation and Path Planning With Multicopters</title><author>Huang, Jing ; Du, Baihui ; Zhang, Youmin ; Quan, Quan ; Wang, Ban ; Mu, Lingxia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c246t-a3de1970ae7658965c240d53d9667ba45e73fa19c76c496029bf86fa6356b3643</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Collision avoidance</topic><topic>Genetic algorithms</topic><topic>Mission assignment</topic><topic>multicopters</topic><topic>multiple traveling salesman problem (mTSP)</topic><topic>Optimization</topic><topic>Path planning</topic><topic>Pesticides</topic><topic>point cloud</topic><topic>precision spraying</topic><topic>Resource management</topic><topic>Rotary wing aircraft</topic><topic>Spraying</topic><topic>Task analysis</topic><topic>Traveling salesman problem</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huang, Jing</creatorcontrib><creatorcontrib>Du, Baihui</creatorcontrib><creatorcontrib>Zhang, Youmin</creatorcontrib><creatorcontrib>Quan, Quan</creatorcontrib><creatorcontrib>Wang, Ban</creatorcontrib><creatorcontrib>Mu, Lingxia</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEL</collection><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on aerospace and electronic systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huang, Jing</au><au>Du, Baihui</au><au>Zhang, Youmin</au><au>Quan, Quan</au><au>Wang, Ban</au><au>Mu, Lingxia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Pesticide Spraying Mission Allocation and Path Planning With Multicopters</atitle><jtitle>IEEE transactions on aerospace and electronic systems</jtitle><stitle>T-AES</stitle><date>2024-04-01</date><risdate>2024</risdate><volume>60</volume><issue>2</issue><spage>2277</spage><epage>2291</epage><pages>2277-2291</pages><issn>0018-9251</issn><eissn>1557-9603</eissn><coden>IEARAX</coden><abstract>This article presents a mission allocation and path-planning solution for the pesticide spraying mission of dense trees in hilly terrains using cooperative multicopters. The problem is formulated as a single-depot single-end multiple traveling salesman problem (mTSP). Three different algorithms, namely classical mTSP algorithm, Grouping-TSP combined algorithm, and Grouping-TSP decoupled algorithm, are developed to solve the proposed mTSP. Simulation results indicate that the classical mTSP algorithm provides an evenly distributed task allocation while the Grouping-TSP combined algorithm delivers the optimal solution. In addition, the Grouping-TSP decoupled algorithm minimizes computational complexity. Both Grouping-TSP algorithms integrate a subregions segmentation process to guarantee collision avoidance between the multicopters.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TAES.2024.3355028</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-5471-8339</orcidid><orcidid>https://orcid.org/0000-0001-8002-1263</orcidid><orcidid>https://orcid.org/0000-0001-8216-8998</orcidid><orcidid>https://orcid.org/0000-0002-9731-5943</orcidid><orcidid>https://orcid.org/0000-0002-6466-5277</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0018-9251
ispartof IEEE transactions on aerospace and electronic systems, 2024-04, Vol.60 (2), p.2277-2291
issn 0018-9251
1557-9603
language eng
recordid cdi_proquest_journals_3037645855
source IEEE Electronic Library (IEL) Journals
subjects Algorithms
Collision avoidance
Genetic algorithms
Mission assignment
multicopters
multiple traveling salesman problem (mTSP)
Optimization
Path planning
Pesticides
point cloud
precision spraying
Resource management
Rotary wing aircraft
Spraying
Task analysis
Traveling salesman problem
title A Pesticide Spraying Mission Allocation and Path Planning With Multicopters
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-25T12%3A46%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Pesticide%20Spraying%20Mission%20Allocation%20and%20Path%20Planning%20With%20Multicopters&rft.jtitle=IEEE%20transactions%20on%20aerospace%20and%20electronic%20systems&rft.au=Huang,%20Jing&rft.date=2024-04-01&rft.volume=60&rft.issue=2&rft.spage=2277&rft.epage=2291&rft.pages=2277-2291&rft.issn=0018-9251&rft.eissn=1557-9603&rft.coden=IEARAX&rft_id=info:doi/10.1109/TAES.2024.3355028&rft_dat=%3Cproquest_cross%3E3037645855%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c246t-a3de1970ae7658965c240d53d9667ba45e73fa19c76c496029bf86fa6356b3643%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=3037645855&rft_id=info:pmid/&rft_ieee_id=10400918&rfr_iscdi=true