Visual Marker based Multi-Sensor Fusion State Estimation

Abstract : This paper presents the description and experimental results of a versatile Visual Marker based Multi-Sensor Fusion State Estimation that allows to combine a variable optional number of sensors and positioning algorithms in a loosely-coupling fashion, incorporating visual markers to increase its performances. This technique allows an aerial robot to navigate in different environments and carrying out different missions with the same state estimation architecture, exploiting the best from every sensor. The state estimation algorithm has been successfully tested controlling a quadrotor equipped with an extra IMU and a RGB camera used only to detect visual markers. The entire framework runs on an onboard computer, including the controllers and the proposed state estimator. The whole software is made publicly available to the scientific community through an open source implementation.
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IFAC World Congress, Jul 2017, Toulouse, France. Proceedings of the 20th IFAC World Congress, 6p., 2017
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https://hal.laas.fr/hal-01501980
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  • HAL Id : hal-01501980, version 1

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Jose Luis Sanchez-Lopez, Victor Arellano-Quintana, Marco Tognon, Pascual Campoy, Antonio Franchi. Visual Marker based Multi-Sensor Fusion State Estimation. IFAC World Congress, Jul 2017, Toulouse, France. Proceedings of the 20th IFAC World Congress, 6p., 2017. 〈hal-01501980〉

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