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Wildlife Surveillance Using a UAV and Thermal Imagery
Linköping University, Department of Electrical Engineering, Automatic Control.
Linköping University, Department of Electrical Engineering, Automatic Control.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [sv]

På senare år har tjuvjakten på noshörningar resulterat i ett kritiskt lågt bestånd. Detta examensarbete är en del av ett initiativ för att stoppa denna utveckling. Målet är att använda en UAV, utrustad med GPS och attitydsensorer, samt en värmekamera placerad på en gimbal, till att övervaka vilda djur. Genom att använda en värmekamera kan djuren lätt detekteras eftersom de antas vara varmare än sin omgivning. En modell av marken vid testområdet har använts för att möjliggöra positionering av detekterade djur, samt analys av vilka områden på marken som ses av kameran.

Termen övervakning inkluderar detektion av djur, målföljning och planering av rutt för UAV:n. UAV:n ska kunna söka av ett område efter djur. För att göra detta krävs planering av trajektoria för UAV:n samt hur gimbalen ska förflyttas. Flera metoder för detta har utvärderats. UAV:n ska även kunna målfölja djur som har detekterats. Till detta har ett partikelfilter använts. För att associera mätningar till spår har Nearest Neighbor-metoden använts. Djuren detekteras genom att bildbehandla på videoströmmen som ges från värmekameran. För bildbehandlingen har flertalet metoder testats. Dessutom presenteras en omfattande beskrivning av hur en UAV fungerar och är uppbyggd. I denna beskrivs även nödvändiga delar för ett UAV-system. På grund av begränsningar i budgeten har ingen UAV inköpts. Istället har tester utförts från en gondol i Kolmården. Gondolen åker runt i testområdet med en konstant hastighet. Djur kunde lätt detekteras och målföljas givet en kall bakgrund. Då solen värmer upp marken är det svårare att särskilja djuren från marken och fler feldetektioner görs av bildbehandlingen

Abstract [en]

In recent years, the poaching of rhinoceros has decreased its numbers to critical levels. This thesis project is a part of an initiative to stop this development. The aim of this master thesis project is to use a UAV equipped with positioning and attitude sensors as well as a thermal camera, placed onto a gimbal, to perform wildlife surveillance. By using a thermal camera, the animals are easily detected as they are assumed to be warmer than the background.

The term wildlife surveillance includes detection of animals, tracking, and planning of the UAV. The UAV should be able to search an area for animals, for this planning of the UAV trajectory and gimbal attitude is needed. Several approaches for this have been tested, both online and offline planning. The UAV should also be able to track the animals that are detected, for this a particle filter has been used. Here a problem of associating measurements to tracks arises. This has been solved by using the Nearest Neighbor algorithm together with gating. The animals are detected by performing image processing on the images received from the thermal camera. Multiple approaches have been evaluated.

Furthermore, a thoroughly worked description of how a UAV is working as well as how it is built up is presented. Here also necessary parts to make up a full unmanned aerial system are described. This chapter can be seen as a good guide for beginners, to the UAV field, interested in knowing how a UAV works and the most common parts of such a system.

A ground model of Kolmården, where the testing has been conducted, has been used in this thesis. The use of this enables positioning of the detected animals and checking if an area is occluded for the camera. Unfortunately, due to budget limitations, no UAV was purchased. Instead, testing has been conducted from a gondola in Kolmården traveling across the test area with a constant speed. To use the gondola as the platform, for the sensors and the thermal camera, is essentially the same as using a UAV as both alternatives are located in the air above the animals, both are traveling around the map and both are stable for good weather conditions.

The animals could easily be detected and tracked given a cold background. When the sun heats up the ground, it is harder to distinguish the animals in the thermal video, and more false detections in the image processing appear.

Place, publisher, year, edition, pages
2016. , 116 p.
Keyword [en]
drone, UAV, UAS, gimbal, autonomous, wildlife surveillance, tracking, planning, thermal, particle filter
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-129586ISRN: LiTH-ISY-EX--16/4968--SEOAI: oai:DiVA.org:liu-129586DiVA: diva2:941275
Subject / course
Automatic Control
Presentation
2016-06-07, Linköping, 14:15 (Swedish)
Supervisors
Examiners
Available from: 2016-06-22 Created: 2016-06-22 Last updated: 2016-06-22Bibliographically approved

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CiteExportLink to record
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