Drones are fast becoming the leading technology in the world of mobile robotics. In fact, these are already used in many outdoor applications, on the contrary, their use in indoor environments is very limited. A major cause comes from the fact that GPS doesn't work well in structured indoor environments. As a result, alternative localization methods are needed, such as those based on fiducial markers. The aim of the project is to evaluate the performance of localization algorithms based on the recognition and identification of different types of markers, in order to identify the best choice.
I droni stanno rapidamente diventando la tecnologia di punta nel mondo della robotica mobile. Questi infatti sono già utilizzati in molte applicazioni outdoor, al contrario, il loro utilizzo in ambienti indoor è molto limitato. Una delle principali cause deriva dal fatto che il GPS non funziona bene in ambienti interni strutturati. Di conseguenza, si rendono necessari metodi di localizzazione alternativi, come, ad esempio, quelli basati sui fiducial markers. Lo scopo del progetto è quello di valutare le prestazioni di algoritmi di localizzazione basati sul riconoscimento e l'identificazione di markers di diverso tipo, al fine identificare la scelta migliore.
Tecniche di localizzazione indoor per droni basate su fiducial markers
KUMAR, SAURAV
2021/2022
Abstract
Drones are fast becoming the leading technology in the world of mobile robotics. In fact, these are already used in many outdoor applications, on the contrary, their use in indoor environments is very limited. A major cause comes from the fact that GPS doesn't work well in structured indoor environments. As a result, alternative localization methods are needed, such as those based on fiducial markers. The aim of the project is to evaluate the performance of localization algorithms based on the recognition and identification of different types of markers, in order to identify the best choice.File | Dimensione | Formato | |
---|---|---|---|
Kumar_Saurav.pdf
accesso aperto
Dimensione
3.91 MB
Formato
Adobe PDF
|
3.91 MB | Adobe PDF | Visualizza/Apri |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
https://hdl.handle.net/20.500.12608/38781