Geometrijske meritve strehe s pomočjo brezpilotnega letalnika

diplomsko delo Visokošolskega strokovnega študijskega programa I. stopnje Strojništvo

Jan Štefin (Author), Janko Slavič (Mentor), Matija Jezeršek (Co-mentor)

Abstract

V diplomski nalogi so predstavljene meritve strehe, ki so bile izmerjene z uporabo brezpilotnega letalnika in lastne Python kode. Ozadje meritev temelji na določanju koordinat preko hitrosti in časa. Preko metode Scale-Invariant Feature Transform so glede na okoliške točke na dveh različnih slikah bili poiskani ujemajoči se deli ter odstranjene točke, neskladne z izbranim modelom slikanja z več pogledi. Poiskane oziroma izračunane so bile tudi rotacijske in translacijske matrike in s pomočjo triangulacije je rekonstruirana lega opazovanih točk v 3D koordinatnem sistemu. Na koncu je bila določena razdalja le med izbranimi točkami, ki ležijo na robu strehe. Rezultat diplomske naloge so meritve strehe, ki jih s pomočjo Pyhton kode program samodejno določi, odstopanja od dejanskih meritev pa v povprečji niso večja kot pol metra.

Keywords

diplomske naloge;brezpilotni letalnik;računalniški vid;umetna inteligenca;meritve strehe;OpenCV;SIFT;triangulacija;

Data

Language:	Slovenian
Year of publishing:	2021
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FS - Faculty of Mechanical Engineering
Publisher:	[J. Štefin]
UDC:	629.014.9:004.8:528.3(043.2)
COBISS:	85014019
Views:	515
Downloads:	104
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Geometric measurements of the housing roof using an unmanned aerial vehicle
Secondary abstract:	Our research presents an image-based rooftop measurement system used in an unmanned aerial vehicle controlled by Python code. The background of our measurements was based on spatial data reconstruction, using multiple images taken by an unmanned aerial vehicle, while taking into consideration the known positions of the aircraft. Through the ScaleInvariant Feature Transform method, matching parts in two different images were found, taking into consideration the surrounding points, while disturbing points were removed. The rotation and translation matrices were calculated and triangulation to reconstruct the position of the observed points in a 3D coordinate system was used. Finally, the points located at the very edge of the roof were selected and by that the distance between them was determined. The final task resulted in roof measurements that are automatically determined by the software using Python code, with deviations from ground-truth averaging no more than half a metre.
Secondary keywords:	thesis;unmanned aeriel vehicle;computer vision;artificial intelligence;roof measurement;scale-invariant feature transform;open source computer vison libary;triangulation;
Type (COBISS):	Bachelor thesis/paper
Study programme:	0
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. v Ljubljani, Fak. za strojništvo
Pages:	XXII, 42, [2] str.
ID:	13836595