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A Loosely-Coupled Approach for Metric Scale Estimation in Monocular Vision-Inertial Systems

Abstract : In monocular vision systems, lack of knowledge about metric distances caused by the inherent scale ambiguity can be a strong limitation for some applications. We offer a method for fusing inertial measurements with monocular odometry or tracking to estimate metric distances in inertial-monocular systems and to increase the rate of pose estimates. As we performed the fusion in a loosely-coupled manner, each input block can be easily replaced with one's preference, which makes our method quite flexible. We experimented our method using the ORB-SLAM algorithm for the monocular tracking input and Euler forward integration to process the inertial measurements. We chose sets of data recorded on UAVs to design a suitable system for flying robots.
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Submitted on : Tuesday, January 9, 2018 - 3:26:09 PM
Last modification on : Tuesday, May 28, 2019 - 4:09:15 PM
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Ariane Spaenlehauer, Vincent Frémont, Ahmet Sekercioglu, Isabelle Fantoni. A Loosely-Coupled Approach for Metric Scale Estimation in Monocular Vision-Inertial Systems. IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), Nov 2017, Daegu, South Korea. pp.137-143. ⟨hal-01678915⟩

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