DocumentCode :
3028083
Title :
Vision based MAV navigation in unknown and unstructured environments
Author :
Blösch, Michael ; Weiss, Stephan ; Scaramuzza, Davide ; Siegwart, Roland
Author_Institution :
Autonomous Syst. Lab., ETH Zurich, Zurich, Switzerland
fYear :
2010
fDate :
3-7 May 2010
Firstpage :
21
Lastpage :
28
Abstract :
Within the research on Micro Aerial Vehicles (MAVs), the field on flight control and autonomous mission execution is one of the most active. A crucial point is the localization of the vehicle, which is especially difficult in unknown, GPS-denied environments. This paper presents a novel vision based approach, where the vehicle is localized using a downward looking monocular camera. A state-of-the-art visual SLAM algorithm tracks the pose of the camera, while, simultaneously, building an incremental map of the surrounding region. Based on this pose estimation a LQG/LTR based controller stabilizes the vehicle at a desired setpoint, making simple maneuvers possible like take-off, hovering, setpoint following or landing. Experimental data show that this approach efficiently controls a helicopter while navigating through an unknown and unstructured environment. To the best of our knowledge, this is the first work describing a micro aerial vehicle able to navigate through an unexplored environment (independently of any external aid like GPS or artificial beacons), which uses a single camera as only exteroceptive sensor.
Keywords :
SLAM (robots); aerospace robotics; aircraft control; image sensors; linear quadratic Gaussian control; microrobots; mobile robots; path planning; pose estimation; robot vision; GPS-denied environments; LQG-LTR based controller; autonomous mission execution; downward looking monocular camera; exteroceptive sensor; flight control; micro aerial vehicles; pose estimation; vision based MAV navigation; visual SLAM algorithm; Aerospace control; Aircraft navigation; Attitude control; Cameras; Global Positioning System; Helicopters; Remotely operated vehicles; Robotics and automation; Sliding mode control; Unmanned aerial vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2010 IEEE International Conference on
Conference_Location :
Anchorage, AK
ISSN :
1050-4729
Print_ISBN :
978-1-4244-5038-1
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ROBOT.2010.5509920
Filename :
5509920
Link To Document :
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