diplomsko delo
Franc Oven (Author), Matej Kristan (Mentor)

Abstract

Detekcija ovir z zlivanjem senzorske informacije za avtonomna plovila

Keywords

stereo sistem;3D inferenca;inercijska merilna naprava;horizont;segmentacija;računalništvo;računalništvo in informatika;univerzitetni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [F. Oven]
UDC: 004.93(043.2)
COBISS: 1536127939 Link will open in a new window
Views: 82
Downloads: 19
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: English
Secondary title: Obstacle detection through sensor fusion is unmanned surface vehicles
Secondary abstract: In our diploma thesis we issue a navigation problem of autonomous surface vehicles. Presume we have a vessel appointed with sensors, such as GPS, IMU, compass, a stereo sistem of two cameras and a standalone processing unit that combines sensor data and performs segmentation and planning in real time. We begin by introducing the algorithm of segmentation, that along with help of advanced computer vision methods extracts useful visual information, therefore avoids obstacles in its path (boats, swimmers, buoys). Then, we focus on horizon estimation by taking into account data of innertial measurement unit, with whom we improve the estimation of a sea border. To improve localization of obstacles in front of the vessel, we calculate depth of every pixel in the image. Image pairs are first rectified as we simplify the correspondence search to single dimension. Furthermore, we present, implement and evaluate our methods. We conclude by discussing further work that can be done.
Secondary keywords: stereo system;3D inference;inertial measurement unit;horizon;segmentation;computer science;computer and information science;diploma;
File type: application/pdf
Type (COBISS): Bachelor thesis/paper
Study programme: 1000468
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 58 str.
ID: 8739473