Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Semi-autonomous Drone System for Mapping and Measuring of Agricultural Fields and Forest Stands
Luleå tekniska universitet, Institutionen för system- och rymdteknik.
2018 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

Unmanned Aerial vehicles are increasingly used in many applications and particularlyin agriculture and forestry. This study develops a semi-autonomous quadcopter dronesystem for mapping and measuring of a given area of land, either agricultural fieldor forest stand.

A coverage path planning algorithm which generates an optimal path for coveringthe area to be mapped is developed. The coverage path planning considers threetypes of area configurations: convex polygon area, concave polygon area and finallya general polygon area with holes in its interior. In order to cover the area by thedrone, the dynamic model of the quadcopter system is identified and used to designthe position controller. The drone is programmed and the images collection is carriedout. The resulting images are used in an image mosaicing algorithm, developed bythis study, to build a 2D map of the area of interest.

The resulting system can effectively generate a coverage path in any area whichhas any polygonal shape configuration. The position controller accuracy allows tocollect the images of a given area with specified image overlaps. The images can alsobe used to build the map of the area with accuracy that is acceptable to the currentapplication of mapping agricultural or forest fields.

sted, utgiver, år, opplag, sider
2018. , s. 56
Emneord [en]
UAV mapping, Image Mosaicing, Convex Decomposition, Path Planning
HSV kategori
Identifikatorer
URN: urn:nbn:se:ltu:diva-78108OAI: oai:DiVA.org:ltu-78108DiVA, id: diva2:1415793
Fag / kurs
Student thesis, at least 30 credits
Utdanningsprogram
Space Engineering, master's level (120 credits)
Presentation
2018-08-07, 17:02 (engelsk)
Veileder
Examiner
Tilgjengelig fra: 2020-03-20 Laget: 2020-03-19 Sist oppdatert: 2020-03-20bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric

urn-nbn
Totalt: 97 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf