A novel online model-based wind estimation approach for quadrotor micro air vehicles using low cost MEMS IMUs

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

22 Citations (Scopus)

Abstract

This work extends the drag-force enhanced quadrotor model by denoting the free stream air velocity as the difference between the ground speed and the wind speed. It is demonstrated that a relatively simple nonlinear observer is capable of estimating the local wind components, provided accelerometer and GPS-velocity measurements are available. We perform a wind tunnel experiment at various wind speeds using a quadrotor vehicle with a low-cost Inertial Measurement Unit (IMU) and a motion tracking system to provide accurate ground speed measurements. It is shown that the onboard Extended Kalman Filter (EKF) accurately estimates the wind components.

Original languageEnglish
Title of host publicationIROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2141-2146
Number of pages6
Volume2016-November
ISBN (Electronic)9781509037629
DOIs
Publication statusPublished - 28 Nov 2016
Event2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon, Korea, Republic of
Duration: 9 Oct 201614 Oct 2016
http://www.iros2016.org/

Conference

Conference2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Abbreviated titleIROS 2016
CountryKorea, Republic of
CityDaejeon
Period9/10/1614/10/16
Internet address

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