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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/3U2TMQB
Repositorysid.inpe.br/sibgrapi/2019/09.11.20.30
Last Update2019:09.11.20.30.40 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2019/09.11.20.30.40
Metadata Last Update2022:06.14.00.09.37 (UTC) administrator
DOI10.1109/SIBGRAPI.2019.00036
Citation KeyAmorimMutSouBadOli:2019:SiEfLo
TitleSimple and effective load volume estimation in moving trucks using LiDARs
FormatOn-line
Year2019
Access Date2024, Apr. 27
Number of Files1
Size4754 KiB
2. Context
Author1 Amorim, Lucas Luppi
2 Mutz, Filipe
3 De Souza, Alberto Ferreira
4 Badue, Claudine
5 Oliveira-Santos, Thiago
Affiliation1 Universidade Federal do Espírito Santo
2 Universidade Federal do Espírito Santo, Instituto Federal do Espírito Santo
3 Universidade Federal do Espírito Santo
4 Universidade Federal do Espírito Santo
5 Universidade Federal do Espírito Santo
EditorOliveira, Luciano Rebouças de
Sarder, Pinaki
Lage, Marcos
Sadlo, Filip
e-Mail Addresslucasluppiam@gmail.com
Conference NameConference on Graphics, Patterns and Images, 32 (SIBGRAPI)
Conference LocationRio de Janeiro, RJ, Brazil
Date28-31 Oct. 2019
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2019-09-11 20:30:40 :: lucasluppiam@gmail.com -> administrator ::
2022-06-14 00:09:37 :: administrator -> lucasluppiam@gmail.com :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsvolume estimation
point cloud registration
mesh reconstruction
truck load measurement
LiDAR
GICP
AbstractIndustries need to track the amount of materials and goods transported through processing units in order to optimize production. In large-scale industries, trucks and trains are commonly used for transportation. The manual evaluation of the volume of material being transported by these vehicles can be imprecise, inefficient, and even unsafe for employees. Therefore, this work presents an automated system for estimating the volume of load in moving trucks using a pair of multi-layer light detection and ranging (LiDAR) sensors. The sensors are mounted in a structure so that trucks can pass through without stopping. The proposed system can be used with any type of compact load such as grains, and powders. A mesh of the load is built and used for estimating the volume. A simple, efficient, and effective heuristic is proposed for tracking the trucks positions. The system was deployed and evaluated in a mining company in real conditions of operation. Experimental results indicate that the system produces accurate estimates of the volume of ore powder transported by trucks. The reconstruction of the loads and the estimative of their volumes are performed once the data is acquired and lasts less than 1.5 minutes on average.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2019 > Simple and effective...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/3U2TMQB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/3U2TMQB
Languageen
Target File123.pdf
User Grouplucasluppiam@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/3UA4FNL
8JMKD3MGPEW34M/3UA4FPS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2019/10.25.18.30.33 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume
7. Description control
e-Mail (login)lucasluppiam@gmail.com
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