Vision-Aided State Estimator for Positioning UAVs

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


Recent developments of UAVs have sparked interest in building UAV-based magnetic surveying systems. Due to the sensitivity of magnetic sensors, direct positioning the magnetometer via traditional devices, e.g., GNSS and UWB, is not possible. However, to get obtain georeferenced data, it is necessary to localize the payload accurately. This paper presents the sensor fusion technique used for the development of an accurate vision-based positioning solution. The sensor fusion module builds upon a square-root unscented Kalman filter to fuse the relative positioning results computed by a monocular camera with the global positioning results from a GNSS/IMU system to determine a target's global positions. The developed method has been validated by real flight experiments. Experimental results show it can provide accurate position estimations, achieving single-axis centimeter-level positioning accuracy and decimeter-level overall 3D positioning accuracy.

Original languageEnglish
Title of host publication2021 International Conference on Unmanned Aircraft Systems (ICUAS 2021)
Publication date2021
Article number9476816
ISBN (Electronic)978-0-7381-3115-3, 978-1-6654-1535-4
Publication statusPublished - 2021
Event2021 International Conference on Unmanned Aircraft Systems (ICUAS '21) - Divani Caravel Hotel, Athens, Greece
Duration: 15 Jun 202118 Jun 2021


Conference2021 International Conference on Unmanned Aircraft Systems (ICUAS '21)
LocationDivani Caravel Hotel


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