DocumentCode :
622394
Title :
A vision and GPS-based real-time trajectory planning for MAV in unknown urban environments
Author :
Flores, Guadalupe ; Shuting Zhou ; Lozano, Rogelio ; Castillo, Pedro
Author_Institution :
Heudiasyc Lab., Univ. of Technol. of Compi`egne, Compiègne, France
fYear :
2013
fDate :
28-31 May 2013
Firstpage :
1150
Lastpage :
1155
Abstract :
This paper addresses the issue of real-time optimal trajectory generation of a micro Air Vehicle (MAV) in unknown urban environments. The MAV is required to navigate from an initial and outdoor position to a final position inside a building. To achieve this objective, we develop a safe path planning method using the information provided by the GPS and a consumer depth camera. With the purpose to develop a safe path planning with obstacle avoidance capabilities, a model predictive control approach is developed, which uses the environment information acquired by the navigation system.
Keywords :
Global Positioning System; aerospace computing; autonomous aerial vehicles; cameras; collision avoidance; control engineering computing; predictive control; robot vision; trajectory control; GPS-based real-time trajectory planning; MAV; consumer depth camera; environment information; micro air vehicle; navigation system; obstacle avoidance capabilities; path planning method; predictive control approach; real-time optimal trajectory generation; unknown urban environments; vision-based real-time trajectory planning; Cameras; Estimation; Feature extraction; Global Positioning System; Real-time systems; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Unmanned Aircraft Systems (ICUAS), 2013 International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4799-0815-8
Type :
conf
DOI :
10.1109/ICUAS.2013.6564806
Filename :
6564806
Link To Document :
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