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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Unmanned Aircraft Systems (ICUAS), 2013 International Conference on
         
        
            Conference_Location : 
Atlanta, GA
         
        
            Print_ISBN : 
978-1-4799-0815-8
         
        
        
            DOI : 
10.1109/ICUAS.2013.6564806