Semi-autonomous Drone System for Mapping and Measuring of Agricultural Fields and Forest Stands
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesis
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.
Place, publisher, year, edition, pages
2018. , p. 56
Keywords [en]
UAV mapping, Image Mosaicing, Convex Decomposition, Path Planning
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-78108OAI: oai:DiVA.org:ltu-78108DiVA, id: diva2:1415793
Subject / course
Student thesis, at least 30 credits
Educational program
Space Engineering, master's level (120 credits)
Presentation
2018-08-07, 17:02 (English)
Supervisors
Examiners
2020-03-202020-03-192020-03-20Bibliographically approved