Show simple item record

dc.contributor.authorSantamaria Navarro, Àngel
dc.contributor.authorSolà Ortega, Joan
dc.contributor.authorAndrade-Cetto, Juan
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2016-03-16T18:23:06Z
dc.date.available2016-03-16T18:23:06Z
dc.date.issued2015
dc.identifier.citationSantamaria, A., Solá, J., Andrade-Cetto, J. High-frequency MAV state estimation using low-cost inertial and optical flow measurement units. A: IEEE/RSJ International Conference on Intelligent Robots and Systems. "2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015, Hamburg, Germany, September 28-October 2, 2015". Hamburg: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 1864-1871.
dc.identifier.isbn978-1-4799-9994-1
dc.identifier.urihttp://hdl.handle.net/2117/84560
dc.descriptionThe paper has supplementary downloadable material available at http://ieeexplore.ieee.org, provided by the authors. The material includes a video of the state estimation presented in the paper.
dc.description.abstractThis paper develops a new method for 3D, high rate vehicle state estimation, specially designed for free-flying Micro Aerial Vehicles (MAVs). We fuse observations from inertial and optical flow low-cost measurement units, and extend the current use of this optical sensors from hovering purposes to odometry estimation. Two Kalman filters, with its extended and error-state versions, are developed, and benchmarked alongside a large number of algorithm variations, using both simulations and real experiments with precise ground-truth. In contrast to state-of-the-art visual-inertial odometry methods, the proposed solution does not require image processing in the main CPU. Instead, the data correction is done taking advantage of the recently appeared optical flow sensors, which directly provide metric information about the MAV motion. We hence reduce the computational load of the main processor unit, and obtain an accurate estimation of the vehicle state at a high update rate.
dc.format.extent8 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Robòtica
dc.subject.otheraerospace robotics
dc.subject.othermobile robots
dc.subject.othersensor fusion
dc.subject.otherfiltering
dc.subject.otherstate estimation
dc.titleHigh-frequency MAV state estimation using low-cost inertial and optical flow measurement units
dc.typeConference report
dc.contributor.groupUniversitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents
dc.identifier.doi10.1109/IROS.2015.7353621
dc.description.peerreviewedPeer Reviewed
dc.subject.inspecClassificació INSPEC::Automation::Robots::Mobile robots
dc.relation.publisherversionhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7353621
dc.rights.accessOpen Access
drac.iddocument17432147
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/287617/EU/Aerial Robotics Cooperative Assembly System/ARCAS
upcommons.citation.authorSantamaria, A.; Solá, J.; Andrade-Cetto, J.
upcommons.citation.contributorIEEE/RSJ International Conference on Intelligent Robots and Systems
upcommons.citation.pubplaceHamburg
upcommons.citation.publishedtrue
upcommons.citation.publicationName2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015, Hamburg, Germany, September 28-October 2, 2015
upcommons.citation.startingPage1864
upcommons.citation.endingPage1871


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain