DocumentCode :
2583850
Title :
Camera-based navigation of a low-cost quadrocopter
Author :
Engel, Jakob ; Sturm, Jürgen ; Cremers, Daniel
Author_Institution :
Dept. of Comput. Sci., Tech. Univ. of Munich, Munich, Germany
fYear :
2012
fDate :
7-12 Oct. 2012
Firstpage :
2815
Lastpage :
2821
Abstract :
In this paper, we describe a system that enables a low-cost quadrocopter coupled with a ground-based laptop to navigate autonomously in previously unknown and GPS-denied environments. Our system consists of three components: a monocular SLAM system, an extended Kalman filter for data fusion and state estimation and a PID controller to generate steering commands. Next to a working system, the main contribution of this paper is a novel, closed-form solution to estimate the absolute scale of the generated visual map from inertial and altitude measurements. In an extensive set of experiments, we demonstrate that our system is able to navigate in previously unknown environments at absolute scale without requiring artificial markers or external sensors. Furthermore, we show (1) its robustness to temporary loss of visual tracking and significant delays in the communication process, (2) the elimination of odometry drift as a result of the visual SLAM system and (3) accurate, scale-aware pose estimation and navigation.
Keywords :
Kalman filters; SLAM (robots); helicopters; image sensors; mobile robots; pose estimation; robot vision; sensor fusion; three-term control; GPS-denied environments; PID controller; artificial markers; camera-based navigation; closed-form solution; data fusion; extended Kalman filter; external sensors; ground-based laptop; low-cost quadrocopter; monocular SLAM system; scale-aware pose estimation; state estimation; steering commands; visual map; Accuracy; Cameras; Delay; Navigation; Simultaneous localization and mapping; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on
Conference_Location :
Vilamoura
ISSN :
2153-0858
Print_ISBN :
978-1-4673-1737-5
Type :
conf
DOI :
10.1109/IROS.2012.6385458
Filename :
6385458
Link To Document :
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