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Self-motion and wind velocity estimation for small-scale UAVs
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-6855-5868
2011 (English)In: 2011 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2011, 1166-1171 p.Conference paper, Published paper (Refereed)
Abstract [en]

For small-scale Unmanned Aerial Vehicles (UAV) to operate indoor, in urban canyons or other scenarios where signals from global navigation satellite systems are denied or impaired, alternative estimation and control strategies must be applied. In this paper a system is proposed that estimates the self-motion and wind velocity by fusing information from airspeed sensors, an inertial measurement unit (IMU) and a monocular camera. Such estimates can be used in control systems for managing wind disturbances or chemical plume based tracking strategies. Simulation results indicate that while the inertial dead-reckoning process is subject to drift, the system is capable of separating the self-motion and wind velocity from the airspeed information.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011. 1166-1171 p.
Keyword [en]
Cameras, Covariance matrix, Estimation, Feature extraction, Noise, Sensors, Visualization
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-32325DOI: 10.1109/ICRA.2011.5979676ISI: 000324383400052Scopus ID: 2-s2.0-84871683833ISBN: 978-1-61284-386-5 (print)OAI: oai:DiVA.org:kth-32325DiVA: diva2:410040
Conference
IEEE International Conference on Robotics and Automation (ICRA). Shanghai, China. May 9-13 2011
Funder
ICT - The Next Generation
Note

QC 20110412

Available from: 2012-11-13 Created: 2011-04-12 Last updated: 2014-09-30Bibliographically approved
In thesis
1. Fusing Visual and Inertial Information
Open this publication in new window or tab >>Fusing Visual and Inertial Information
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2011. vii, 21 p.
Series
Trita-EE, ISSN 1653-5146 ; 2011:023
Keyword
sensor fusion, inertial measurement unit, monocular camera, inertial navigation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-32112 (URN)978-91-7415-919-6 (ISBN)
Presentation
2011-04-05, Q2, KTH Royal Institute of Technology, Stockholm, 13:15 (English)
Opponent
Supervisors
Note
QC 20110412Available from: 2011-04-12 Created: 2011-04-06 Last updated: 2011-04-12Bibliographically approved

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