Hybrid machine learning VDM for UAV's in GNSS denied environment/ Shady Zahran
Material type: TextPublication details: 2018Subject(s): In: Navigation : Vol 65 No 3, Fall 2018, pp.477-492 (43)Summary: This paper presents a novel approach to enhance unmanned aerial vehicle (UAV) autonomous navigation. UAVs play an important role in a wide variety of activities in different fields of military and civilian applications. Researchers have focused their efforts in different categories of research areas to achieve a fully automated UAV in different circumstances and environments such as sensor fusion, communication, path planning, and trajectory generation.Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
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Journal Article | Mindef Library & Info Centre Journals | UNMANNED AERIAL VEHICLE (Browse shelf(Opens below)) | 1 | Not for loan | 61894-1001 |
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UNMANED AIRCRAFT SYSTEMS Transforming in contact: building highly lethal unmanned professionals/ | UNMANNED AERIAL SYSTEM Above and beyond the trenches/ | UNMANNED AERIAL SYSTEMS Unmanned aerial systems in the land environment/ | UNMANNED AERIAL VEHICLE Hybrid machine learning VDM for UAV's in GNSS denied environment/ | UNMANNED AERIAL VEHICLE Asia-Pacific unmanned aerial vehicle directory 2019/ | UNMANNED AERIAL VEHICLES Shrink to fit : sensors developed for UAVs offer surveillance revolution / | UNMANNED AERIAL VEHICLES Drones : complete guide |
This paper presents a novel approach to enhance unmanned aerial vehicle (UAV) autonomous navigation. UAVs play an important role in a wide variety of activities in different fields of military and civilian applications. Researchers have focused their efforts in different categories of research areas to achieve a fully automated UAV in different circumstances and environments such as sensor fusion, communication, path planning, and trajectory generation.
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