Autonomous Full 3D Coverage Using an Aerial Vehicle, Performing Localization, Path Planning, and Navigation towards Indoors Inventorying for the Logistics Domain

Over the last years, a rapid evolution of unmanned aerial vehicle (UAV) usage in various applications has been observed. Their use in indoor environments requires a precise perception of the surrounding area, immediate response to its changes, and, consequently, a robust position estimation. This pa...

Full description

Saved in:
Bibliographic Details
Published in:Robotics (Basel) 2024-06, Vol.13 (6), p.83
Main Authors: Tsiakas, Kosmas, Tsardoulias, Emmanouil, Symeonidis, Andreas L.
Format: Article
Language:English
Subjects:
3D coverage
Algorithms
Cameras
Drone aircraft
Drones
Global positioning systems
GPS
Indoor environments
Inertial platforms
Inertial sensing devices
inventorying
Localization
Location-based systems
Logistics
Logistics services
Navigation
particle filter
Path planning
Planning
Proportional integral derivative
Radio frequency identification
Robotics
Robots
Sensor arrays
Sensors
Technology application
UAV
Unmanned aerial vehicles
Vehicles
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-c301t-6c9b5136c67853363c71068c5aa3c6443bacbcc81c267117c98b9a0535ae29653
container_end_page
container_issue 6
container_start_page 83
container_title Robotics (Basel)
container_volume 13
creator Tsiakas, Kosmas
Tsardoulias, Emmanouil
Symeonidis, Andreas L.
description Over the last years, a rapid evolution of unmanned aerial vehicle (UAV) usage in various applications has been observed. Their use in indoor environments requires a precise perception of the surrounding area, immediate response to its changes, and, consequently, a robust position estimation. This paper provides an implementation of navigation algorithms for solving the problem of fast, reliable, and low-cost inventorying in the logistics industry. The drone localization is achieved with a particle filter algorithm that uses an array of distance sensors and an inertial measurement unit (IMU) sensor. Navigation is based on a proportional–integral–derivative (PID) position controller that ensures an obstacle-free path within the known 3D map. As for the full 3D coverage, an extraction of the targets and then their final succession towards optimal coverage is performed. Finally, a series of experiments are carried out to examine the robustness of the positioning system using different motion patterns and velocities. At the same time, various ways of traversing the environment are examined by using different configurations of the sensor that is used to perform the area coverage.
doi_str_mv 10.3390/robotics13060083
format article
fullrecord <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_c8bd9f3897384a1aaa5995a8858774ea</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A799654179</galeid><doaj_id>oai_doaj_org_article_c8bd9f3897384a1aaa5995a8858774ea</doaj_id><sourcerecordid>A799654179</sourcerecordid><originalsourceid>FETCH-LOGICAL-c301t-6c9b5136c67853363c71068c5aa3c6443bacbcc81c267117c98b9a0535ae29653</originalsourceid><addsrcrecordid>eNpdkk1v1DAQhiMEElXpnaMlrt1ir-Ov42pLYaUV9EC5RhPHyXqVeIrtLCr_hn-K00UIYR9mNO_Mo3ekqaq3jN5wbuj7iC1mbxPjVFKq-YvqYr1meiWFZi__yV9XVykdaXmGcS3ZRfVrM2cMOOGcyN08joTfki2eXITBkYfkw0AgkI2LHkbyzR28Hd01uXexxzgt6h4tjP4nZI-hCJAP5H6EEIp2XUY78hlOfniWScYfELtEdqFDjEs8uZAxPi2gAiT54Apw8GlZhtziBD68qV71MCZ39SdeVg93H75uP632Xz7utpv9ynLK8kpa0wrGpZVKC84lt4pRqa0A4FbWNW_BttZqZtdSMaas0a0BKrgAtzZS8Mtqd-Z2CMfmMfoJ4lOD4JvnAsahgZiX_Rur2870XBvFdQ0MAIQxArQWWqnaQWG9O7MeI36fXcrNEecYiv2GU1UM1IzR0nVz7hqgQH3oMUew5Xdu8haD632pb5Qp9mqmTBmg5wEbMaXo-r82GW2WQ2j-PwT-G2sxqHI</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3072674110</pqid></control><display><type>article</type><title>Autonomous Full 3D Coverage Using an Aerial Vehicle, Performing Localization, Path Planning, and Navigation towards Indoors Inventorying for the Logistics Domain</title><source>ProQuest - Publicly Available Content Database</source><creator>Tsiakas, Kosmas ; Tsardoulias, Emmanouil ; Symeonidis, Andreas L.</creator><creatorcontrib>Tsiakas, Kosmas ; Tsardoulias, Emmanouil ; Symeonidis, Andreas L.</creatorcontrib><description>Over the last years, a rapid evolution of unmanned aerial vehicle (UAV) usage in various applications has been observed. Their use in indoor environments requires a precise perception of the surrounding area, immediate response to its changes, and, consequently, a robust position estimation. This paper provides an implementation of navigation algorithms for solving the problem of fast, reliable, and low-cost inventorying in the logistics industry. The drone localization is achieved with a particle filter algorithm that uses an array of distance sensors and an inertial measurement unit (IMU) sensor. Navigation is based on a proportional–integral–derivative (PID) position controller that ensures an obstacle-free path within the known 3D map. As for the full 3D coverage, an extraction of the targets and then their final succession towards optimal coverage is performed. Finally, a series of experiments are carried out to examine the robustness of the positioning system using different motion patterns and velocities. At the same time, various ways of traversing the environment are examined by using different configurations of the sensor that is used to perform the area coverage.</description><identifier>ISSN: 2218-6581</identifier><identifier>EISSN: 2218-6581</identifier><identifier>DOI: 10.3390/robotics13060083</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>3D coverage ; Algorithms ; Cameras ; Drone aircraft ; Drones ; Global positioning systems ; GPS ; Indoor environments ; Inertial platforms ; Inertial sensing devices ; inventorying ; Localization ; Location-based systems ; Logistics ; Logistics services ; Navigation ; particle filter ; Path planning ; Planning ; Proportional integral derivative ; Radio frequency identification ; Robotics ; Robots ; Sensor arrays ; Sensors ; Technology application ; UAV ; Unmanned aerial vehicles ; Vehicles</subject><ispartof>Robotics (Basel), 2024-06, Vol.13 (6), p.83</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. 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/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c301t-6c9b5136c67853363c71068c5aa3c6443bacbcc81c267117c98b9a0535ae29653</cites><orcidid>0000-0001-9034-4832 ; 0000-0003-0235-6046 ; 0000-0003-2580-4446</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3072674110/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3072674110?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Tsiakas, Kosmas</creatorcontrib><creatorcontrib>Tsardoulias, Emmanouil</creatorcontrib><creatorcontrib>Symeonidis, Andreas L.</creatorcontrib><title>Autonomous Full 3D Coverage Using an Aerial Vehicle, Performing Localization, Path Planning, and Navigation towards Indoors Inventorying for the Logistics Domain</title><title>Robotics (Basel)</title><description>Over the last years, a rapid evolution of unmanned aerial vehicle (UAV) usage in various applications has been observed. Their use in indoor environments requires a precise perception of the surrounding area, immediate response to its changes, and, consequently, a robust position estimation. This paper provides an implementation of navigation algorithms for solving the problem of fast, reliable, and low-cost inventorying in the logistics industry. The drone localization is achieved with a particle filter algorithm that uses an array of distance sensors and an inertial measurement unit (IMU) sensor. Navigation is based on a proportional–integral–derivative (PID) position controller that ensures an obstacle-free path within the known 3D map. As for the full 3D coverage, an extraction of the targets and then their final succession towards optimal coverage is performed. Finally, a series of experiments are carried out to examine the robustness of the positioning system using different motion patterns and velocities. At the same time, various ways of traversing the environment are examined by using different configurations of the sensor that is used to perform the area coverage.</description><subject>3D coverage</subject><subject>Algorithms</subject><subject>Cameras</subject><subject>Drone aircraft</subject><subject>Drones</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>Indoor environments</subject><subject>Inertial platforms</subject><subject>Inertial sensing devices</subject><subject>inventorying</subject><subject>Localization</subject><subject>Location-based systems</subject><subject>Logistics</subject><subject>Logistics services</subject><subject>Navigation</subject><subject>particle filter</subject><subject>Path planning</subject><subject>Planning</subject><subject>Proportional integral derivative</subject><subject>Radio frequency identification</subject><subject>Robotics</subject><subject>Robots</subject><subject>Sensor arrays</subject><subject>Sensors</subject><subject>Technology application</subject><subject>UAV</subject><subject>Unmanned aerial vehicles</subject><subject>Vehicles</subject><issn>2218-6581</issn><issn>2218-6581</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkk1v1DAQhiMEElXpnaMlrt1ir-Ov42pLYaUV9EC5RhPHyXqVeIrtLCr_hn-K00UIYR9mNO_Mo3ekqaq3jN5wbuj7iC1mbxPjVFKq-YvqYr1meiWFZi__yV9XVykdaXmGcS3ZRfVrM2cMOOGcyN08joTfki2eXITBkYfkw0AgkI2LHkbyzR28Hd01uXexxzgt6h4tjP4nZI-hCJAP5H6EEIp2XUY78hlOfniWScYfELtEdqFDjEs8uZAxPi2gAiT54Apw8GlZhtziBD68qV71MCZ39SdeVg93H75uP632Xz7utpv9ynLK8kpa0wrGpZVKC84lt4pRqa0A4FbWNW_BttZqZtdSMaas0a0BKrgAtzZS8Mtqd-Z2CMfmMfoJ4lOD4JvnAsahgZiX_Rur2870XBvFdQ0MAIQxArQWWqnaQWG9O7MeI36fXcrNEecYiv2GU1UM1IzR0nVz7hqgQH3oMUew5Xdu8haD632pb5Qp9mqmTBmg5wEbMaXo-r82GW2WQ2j-PwT-G2sxqHI</recordid><startdate>20240601</startdate><enddate>20240601</enddate><creator>Tsiakas, Kosmas</creator><creator>Tsardoulias, Emmanouil</creator><creator>Symeonidis, Andreas L.</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>7XB</scope><scope>8AL</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9034-4832</orcidid><orcidid>https://orcid.org/0000-0003-0235-6046</orcidid><orcidid>https://orcid.org/0000-0003-2580-4446</orcidid></search><sort><creationdate>20240601</creationdate><title>Autonomous Full 3D Coverage Using an Aerial Vehicle, Performing Localization, Path Planning, and Navigation towards Indoors Inventorying for the Logistics Domain</title><author>Tsiakas, Kosmas ; Tsardoulias, Emmanouil ; Symeonidis, Andreas L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c301t-6c9b5136c67853363c71068c5aa3c6443bacbcc81c267117c98b9a0535ae29653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>3D coverage</topic><topic>Algorithms</topic><topic>Cameras</topic><topic>Drone aircraft</topic><topic>Drones</topic><topic>Global positioning systems</topic><topic>GPS</topic><topic>Indoor environments</topic><topic>Inertial platforms</topic><topic>Inertial sensing devices</topic><topic>inventorying</topic><topic>Localization</topic><topic>Location-based systems</topic><topic>Logistics</topic><topic>Logistics services</topic><topic>Navigation</topic><topic>particle filter</topic><topic>Path planning</topic><topic>Planning</topic><topic>Proportional integral derivative</topic><topic>Radio frequency identification</topic><topic>Robotics</topic><topic>Robots</topic><topic>Sensor arrays</topic><topic>Sensors</topic><topic>Technology application</topic><topic>UAV</topic><topic>Unmanned aerial vehicles</topic><topic>Vehicles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tsiakas, Kosmas</creatorcontrib><creatorcontrib>Tsardoulias, Emmanouil</creatorcontrib><creatorcontrib>Symeonidis, Andreas L.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aluminium Industry Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Engineering Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest - Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>Directory of Open Access Journals (Open Access)</collection><jtitle>Robotics (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tsiakas, Kosmas</au><au>Tsardoulias, Emmanouil</au><au>Symeonidis, Andreas L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Autonomous Full 3D Coverage Using an Aerial Vehicle, Performing Localization, Path Planning, and Navigation towards Indoors Inventorying for the Logistics Domain</atitle><jtitle>Robotics (Basel)</jtitle><date>2024-06-01</date><risdate>2024</risdate><volume>13</volume><issue>6</issue><spage>83</spage><pages>83-</pages><issn>2218-6581</issn><eissn>2218-6581</eissn><abstract>Over the last years, a rapid evolution of unmanned aerial vehicle (UAV) usage in various applications has been observed. Their use in indoor environments requires a precise perception of the surrounding area, immediate response to its changes, and, consequently, a robust position estimation. This paper provides an implementation of navigation algorithms for solving the problem of fast, reliable, and low-cost inventorying in the logistics industry. The drone localization is achieved with a particle filter algorithm that uses an array of distance sensors and an inertial measurement unit (IMU) sensor. Navigation is based on a proportional–integral–derivative (PID) position controller that ensures an obstacle-free path within the known 3D map. As for the full 3D coverage, an extraction of the targets and then their final succession towards optimal coverage is performed. Finally, a series of experiments are carried out to examine the robustness of the positioning system using different motion patterns and velocities. At the same time, various ways of traversing the environment are examined by using different configurations of the sensor that is used to perform the area coverage.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/robotics13060083</doi><orcidid>https://orcid.org/0000-0001-9034-4832</orcidid><orcidid>https://orcid.org/0000-0003-0235-6046</orcidid><orcidid>https://orcid.org/0000-0003-2580-4446</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2218-6581
ispartof Robotics (Basel), 2024-06, Vol.13 (6), p.83
issn 2218-6581
2218-6581
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_c8bd9f3897384a1aaa5995a8858774ea
source ProQuest - Publicly Available Content Database
subjects 3D coverage
Algorithms
Cameras
Drone aircraft
Drones
Global positioning systems
GPS
Indoor environments
Inertial platforms
Inertial sensing devices
inventorying
Localization
Location-based systems
Logistics
Logistics services
Navigation
particle filter
Path planning
Planning
Proportional integral derivative
Radio frequency identification
Robotics
Robots
Sensor arrays
Sensors
Technology application
UAV
Unmanned aerial vehicles
Vehicles
title Autonomous Full 3D Coverage Using an Aerial Vehicle, Performing Localization, Path Planning, and Navigation towards Indoors Inventorying for the Logistics Domain
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T14%3A03%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Autonomous%20Full%203D%20Coverage%20Using%20an%20Aerial%20Vehicle,%20Performing%20Localization,%20Path%20Planning,%20and%20Navigation%20towards%20Indoors%20Inventorying%20for%20the%20Logistics%20Domain&rft.jtitle=Robotics%20(Basel)&rft.au=Tsiakas,%20Kosmas&rft.date=2024-06-01&rft.volume=13&rft.issue=6&rft.spage=83&rft.pages=83-&rft.issn=2218-6581&rft.eissn=2218-6581&rft_id=info:doi/10.3390/robotics13060083&rft_dat=%3Cgale_doaj_%3EA799654179%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c301t-6c9b5136c67853363c71068c5aa3c6443bacbcc81c267117c98b9a0535ae29653%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=3072674110&rft_id=info:pmid/&rft_galeid=A799654179&rfr_iscdi=true