Model-aided state estimation for quadrotor micro air vehicles amidst wind disturbances

Abeywardena, D; Wang, Z; Dissanayake, G; Waslander, SL; Kodagoda, S

Model-aided state estimation for quadrotor micro air vehicles amidst wind disturbances

Abeywardena, D Wang, Z Dissanayake, G

Waslander, SL Kodagoda, S

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2014, pp. 4813 - 4818
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Abeywardena, D	en_US
dc.contributor.author	Wang, Z	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.contributor.author	Waslander, SL	en_US
dc.contributor.author	Kodagoda, S https://orcid.org/0000-0001-5175-9138	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2014, pp. 4813 - 4818	en_US
dc.identifier.isbn	9781479969340	en_US
dc.identifier.issn	2153-0858	en_US
dc.identifier.uri	http://hdl.handle.net/10453/30529
dc.description.abstract	© 2014 IEEE. This paper extends the recently developed Model-Aided Visual-Inertial Fusion (MA-VIF) technique for quadrotor Micro Air Vehicles (MAV) to deal with wind disturbances. The wind effects are explicitly modelled in the quadrotor dynamic equations excluding the unobservable wind velocity component. This is achieved by a nonlinear observability of the dynamic system with wind effects. We show that using the developed model, the vehicle pose and two components of the wind velocity vector can be simultaneously estimated with a monocular camera and an inertial measurement unit. We also show that the MA-VIF is reasonably tolerant to wind disturbances, even without explicit modelling of wind effects and explain the reasons for this behaviour. Experimental results using a Vicon motion capture system are presented to demonstrate the effectiveness of the proposed method and validate our claims.	en_US
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems	en_US
dc.relation.isbasedon	10.1109/IROS.2014.6943246	en_US
dc.title	Model-aided state estimation for quadrotor micro air vehicles amidst wind disturbances	en_US
dc.type	Conference Proceeding
utslib.for	0913 Mechanical Engineering	en_US
dc.location.activity	Chicago, Illinois
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. This paper extends the recently developed Model-Aided Visual-Inertial Fusion (MA-VIF) technique for quadrotor Micro Air Vehicles (MAV) to deal with wind disturbances. The wind effects are explicitly modelled in the quadrotor dynamic equations excluding the unobservable wind velocity component. This is achieved by a nonlinear observability of the dynamic system with wind effects. We show that using the developed model, the vehicle pose and two components of the wind velocity vector can be simultaneously estimated with a monocular camera and an inertial measurement unit. We also show that the MA-VIF is reasonably tolerant to wind disturbances, even without explicit modelling of wind effects and explain the reasons for this behaviour. Experimental results using a Vicon motion capture system are presented to demonstrate the effectiveness of the proposed method and validate our claims.

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http://hdl.handle.net/10453/30529