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Conference Papers Year : 2017

Image-based UAV localization using Interval Methods


This paper proposes an image-based localization method that enables to estimate a bounded domain of the pose of an unmanned aerial vehicle (UAV) from uncertain measurements of known landmarks in the image. The approach computes a domain that should contain the actual robot pose, assuming bounded image measurement errors and landmark position uncertainty. It relies on interval analysis and constraint propagation techniques to rigorously back-propagate the errors through the non-linear observation model. Attitude information from onboard sensors is merged with image observations to reduce the pose uncertainty domain, along with prediction based on velocity measurements. As tracking landmarks in the image is prone to errors, the proposed method also enable fault detection from measurement inconsistencies. This method is tested using a quadcopter UAV with an onboard camera.
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hal-01572369 , version 1 (07-08-2017)


  • HAL Id : hal-01572369 , version 1


Ide-Flore Kenmogne, Vincent Drevelle, Eric Marchand. Image-based UAV localization using Interval Methods. IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Sep 2017, Vancouver, Canada. pp.5285-5291. ⟨hal-01572369⟩
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