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Field and Service Robotics pp 153–166Cite as

Tightly-Coupled Model Aided Visual-Inertial Fusion for Quadrotor Micro Air Vehicles

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Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 105))

Abstract

The main contribution of this paper is a tightly-coupled visual-inertial fusion algorithm for simultaneous localisation and mapping (SLAM) for a quadrotor micro aerial vehicle (MAV). Proposed algorithm is based on an extended Kalman filter that uses a platform specific dynamic model to integrate information from an inertial measurement unit (IMU) and a monocular camera on board the MAV. MAV dynamic model exploits the unique characteristics of the quadrotor, making it possible to generate relatively accurate motion predictions. This, together with an undelayed feature initialisation strategy based on inverse depth parametrisation enables more effective feature tracking and reliable visual SLAM with a small number of features even during rapid manoeuvres. Experimental results are presented to demonstrate the effectiveness of the proposed algorithm.

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Author information

Authors and Affiliations

  1. Centre Autonomous Systems (CAS), University of Technology, Sydney, Australia

    Dinuka Abeywardena & Gamini Dissanayake

Authors
  1. Dinuka Abeywardena
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  2. Gamini Dissanayake
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Corresponding author

Correspondence to Dinuka Abeywardena .

Editor information

Editors and Affiliations

  1. Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia

    Luis Mejias

  2. Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia

    Peter Corke

  3. Autonomous Systems Laboratory QCAT Technology Court, CSIRO ICT Centre, Pullenvale, Queensland, Australia

    Jonathan Roberts

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Abeywardena, D., Dissanayake, G. (2015). Tightly-Coupled Model Aided Visual-Inertial Fusion for Quadrotor Micro Air Vehicles. In: Mejias, L., Corke, P., Roberts, J. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 105. Springer, Cham. https://doi.org/10.1007/978-3-319-07488-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-07488-7_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07487-0

  • Online ISBN: 978-3-319-07488-7

  • eBook Packages: EngineeringEngineering (R0)

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