Obstacle detection is a fundamental task for Unmanned Aerial Vehicles (UAV) as a part of a Sense and Avoid system. In this study, we present a method of multi-sensor obstacle detection that demonstrated good results on different kind of obstacles. This method can be implemented on low-cost platforms involving a DSP or small FPGA. In this paper, we also present a study on the typical targets that can be tough to detect because of their characteristics of reflectivity, form factor, heterogeneity and show how data fusion can often overcome the limitations of each technology.
Obstacle detection system involving fusion of multiple sensor technologies / Gianni', C.; Balsi, M.; Esposito, S.; Fallavollita, P.. - ELETTRONICO. - 42:2W6(2017), pp. 127-134. (Intervento presentato al convegno 4th ISPRS International Conference on Unmanned Aerial Vehicles in Geomatics, UAV-g 2017 tenutosi a Bonn; Germany nel 2017) [10.5194/isprs-archives-XLII-2-W6-127-2017].
Obstacle detection system involving fusion of multiple sensor technologies
Gianni', C.
Writing – Original Draft Preparation
;Balsi, M.
Supervision
;Esposito, S.
Writing – Review & Editing
;Fallavollita, P.
Membro del Collaboration Group
2017
Abstract
Obstacle detection is a fundamental task for Unmanned Aerial Vehicles (UAV) as a part of a Sense and Avoid system. In this study, we present a method of multi-sensor obstacle detection that demonstrated good results on different kind of obstacles. This method can be implemented on low-cost platforms involving a DSP or small FPGA. In this paper, we also present a study on the typical targets that can be tough to detect because of their characteristics of reflectivity, form factor, heterogeneity and show how data fusion can often overcome the limitations of each technology.File | Dimensione | Formato | |
---|---|---|---|
Gianni_preprint_Obstacle-detection_2017.pdf
accesso aperto
Note: Articolo principale
Tipologia:
Documento in Pre-print (manoscritto inviato all'editore, precedente alla peer review)
Licenza:
Creative commons
Dimensione
3.63 MB
Formato
Adobe PDF
|
3.63 MB | Adobe PDF | |
Gianni_Obstacle-detection_2017.pdf
accesso aperto
Tipologia:
Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza:
Creative commons
Dimensione
3.96 MB
Formato
Adobe PDF
|
3.96 MB | Adobe PDF |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.