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.
Document type :
Conference papers
2017 IFAC World Congress, Jul 2017, Toulouse, France. 6p., 2017
Liste complète des métadonnées

Cited literature [28 references]  Display  Hide  Download

https://hal.laas.fr/hal-01562557
Contributor : Antonio Franchi <>
Submitted on : Saturday, July 15, 2017 - 4:55:06 PM
Last modification on : Thursday, January 11, 2018 - 6:26:55 AM

File

2017h-SanAreTogCamFra-preprint...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01562557, version 1

Citation

Jose Luis Sanchez-Lopez, Victor Arellano-Quintana, Marco Tognon, Pascual Campoy, Antonio Franchi. Visual Marker based Multi-Sensor Fusion State Estimation. 2017 IFAC World Congress, Jul 2017, Toulouse, France. 6p., 2017. 〈hal-01562557〉

Share

Metrics

Record views

41

Files downloads

17