Name
Abstract | ||
|---|---|---|
In this paper, we report on early results of the experimental deployment of localization techniques for a multi-rotor Micro Aerial Vehicle (MAV). In particular, we focus on deployment scenarios where the Global Navigation Satellite System (GNSS) does not provide a reliable signal, and thus it is not desirable to rely solely on the GNSS. There-fore, we consider recent advancements in the visual localization, and we employ an onboard RGB-D camera to develop a robust and reliable solution for the MAV localization in partially GNSS denied operational environments. We consider a localization method based on Kalman filter for data fusion of the vision-based localization with the signal from the GNSS. Based on the reported experimental results, the proposed solution supports the localization of the MAV for the temporarily unavailable GNSS, but also improves the position estimation provided by the incremental vision-based localization system while it can run using onboard computational resources of the small vehicle. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-14984-0_20 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Software deployment,Computer science,Satellite system,Fusion,Real-time computing,Kalman filter,Sensor fusion,RGB color model,GNSS applications,Localization system | Conference | 11472 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.35 |
References | Authors | |
0 | 2 | |