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Survey on Computer Vision for UAVs: Current Developments and Trends
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Number of Authors: 2
2017 (English)In: Journal of Intelligent & Robotic Systems, ISSN 0921-0296Article in journal (Refereed) Epub ahead of print
Abstract [en]

During last decade the scientific research on Unmanned Aerial Vehicless (UAVs) increased spectacularly and led to the design of multiple types of aerial platforms. The major challenge today is the development of autonomously operating aerial agents capable of completing missions independently of human interaction. To this extent, visual sensing techniques have been integrated in the control pipeline of the UAVs in order to enhance their navigation and guidance skills. The aim of this article is to present a comprehensive literature review on vision based applications for UAVs focusing mainly on current developments and trends. These applications are sorted in different categories according to the research topics among various research groups. More specifically vision based position-attitude control, pose estimation and mapping, obstacle detection as well as target tracking are the identified components towards autonomous agents. Aerial platforms could reach greater level of autonomy by integrating all these technologies onboard. Additionally, throughout this article the concept of fusion multiple sensors is highlighted, while an overview on the challenges addressed and future trends in autonomous agent development will be also provided.

Place, publisher, year, edition, pages
2017.
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-61786DOI: 10.1007/s10846-017-0483-zScopusID: 2-s2.0-85010764302OAI: oai:DiVA.org:ltu-61786DiVA: diva2:1070742
Available from: 2017-02-02 Created: 2017-02-02 Last updated: 2017-02-02

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