Visual-inertial fusion for quadrotor Micro Air Vehicles with improved scale observability

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

Visual-inertial fusion for quadrotor Micro Air Vehicles with improved scale observability

Abeywardena, D Wang, Z Kodagoda, S

Dissanayake, G

Permalink

Publication Type:: Conference Proceeding
Citation:: Proceedings - IEEE International Conference on Robotics and Automation, 2013, pp. 3148 - 3153
Issue Date:: 2013-11-14

Closed Access

	Filename	Description	Size
	2012004329OK.pdf		1.17 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Abeywardena, D	en_US
dc.contributor.author	Wang, Z	en_US
dc.contributor.author	Kodagoda, S https://orcid.org/0000-0001-5175-9138	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2013-11-14	en_US
dc.identifier.citation	Proceedings - IEEE International Conference on Robotics and Automation, 2013, pp. 3148 - 3153	en_US
dc.identifier.isbn	9781467356411	en_US
dc.identifier.issn	1050-4729	en_US
dc.identifier.uri	http://hdl.handle.net/10453/27992
dc.description.abstract	This paper presents a novel algorithm for fusing monocular vision and inertial information for quadrotor Micro Air Vehicles by incorporating the unique dynamic characteristics of that platform into the state estimation process. The dynamics of a quadrotor is unique in that a dual axis accelerometer mounted parallel to the propeller plane provides measurements that are directly proportional to vehicle velocities in that plane. By exploiting these dynamic characteristics, we show that all vehicle states, including the absolute scale, become observable in all motion patterns. This distinguishes our method with other visual-inertial fusion methods, which either assume zero accelerometer bias, or require 'sufficiently exciting' motion, such as non-zero acceleration, to ensure observability of the scale. The advantages of our method over existing visual-inertial fusion algorithms are proved through a theoretical analysis using Lie Derivatives and verified by extensive simulations and experiments. © 2013 IEEE.	en_US
dc.relation.ispartof	Proceedings - IEEE International Conference on Robotics and Automation	en_US
dc.relation.isbasedon	10.1109/ICRA.2013.6631015	en_US
dc.title	Visual-inertial fusion for quadrotor Micro Air Vehicles with improved scale observability	en_US
dc.type	Conference Proceeding
utslib.for	0913 Mechanical Engineering	en_US
dc.location.activity	Karlsruhe-Germany	en_US
dc.location.activity	Karlsruhe, GERMANY
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	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper presents a novel algorithm for fusing monocular vision and inertial information for quadrotor Micro Air Vehicles by incorporating the unique dynamic characteristics of that platform into the state estimation process. The dynamics of a quadrotor is unique in that a dual axis accelerometer mounted parallel to the propeller plane provides measurements that are directly proportional to vehicle velocities in that plane. By exploiting these dynamic characteristics, we show that all vehicle states, including the absolute scale, become observable in all motion patterns. This distinguishes our method with other visual-inertial fusion methods, which either assume zero accelerometer bias, or require 'sufficiently exciting' motion, such as non-zero acceleration, to ensure observability of the scale. The advantages of our method over existing visual-inertial fusion algorithms are proved through a theoretical analysis using Lie Derivatives and verified by extensive simulations and experiments. © 2013 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/27992