Vision-Based SLAM System for Small UAVs in GPS-Denied Environments
Publication: Journal of Aerospace Engineering
Volume 25, Issue 4
Abstract
Vision-based unmanned aerial vehicle (UAV) control is a core technology in global positioning system (GPS)-denied environments. However, small UAVs have difficulty processing image data in real time because of their limited payload capacity and relatively weak processor. Development of an image-processing system that is suitable for small UAVs is therefore needed. In this paper, an approach for a vision-based simultaneous localization and mapping (SLAM) system for small UAVs is suggested. For real-time localization, a method wherein Kanade-Lucas-Tomasi-based localization and tracking are performed within small UAVs in real time is adopted. At the same time, scale-invariant feature transform–based mapping and more accurate localization are performed at the ground-control station. A vision-based three-dimensional map-building method for small UAVs using a monocular camera is also proposed. The proposed method first extracts straight-line information from images and calculates their equations in three-dimensional space. It then constructs plane information from line information.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science, and Technology (Grant No. 2010-0011851).
References
Ahrens, S. G. (2008). “Vision-based guidance and control of a hovering vehicle in unknown environments.” M.S. thesis, Massachusetts Institute of Technology, Cambridge, MA.
Bouabdallah, S., Murrieri, P., and Siegwart, R. (2004). “Design and control of an indoor micro quadrotor.” Proc., IEEE Int. Conf. on Robotics and Automation, IEEE, New Orleans, LA, 4393–4398.
Bouguet, J.-Y. (2010). “Camera calibration toolbox for Matlab.” 〈http://www.vision.caltech.edu/bouguetj/calib_doc/〉 (Sep. 20, 2010).
Bradski, G., and Kaehler, A. (2008). Learning OpenCV, O’Reilly, Sebastopol, CA.
Canny, J. (1986). “A computational approach to edge detection.” IEEE Trans. Pattern Anal. Mach. Intell., PAMI-8(6), 679–698.
Celik, K., Chung, S.-J., Clausman, M., and Somani, A. K. (2009). “Monocular vision SLAM for indoor aerial vehicles.” Proc., IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), IEEE, St. Louis, MO, 1566–1573.
Celik, K., Chung, S.-J., and Somani, A. K. (2008). “MVCSLAM: mono-vision corner SLAM for autonomous micro-helicopters in GPS denied environments.” Proc., AIAA Guidance, Navigation and Control Conf. and Exhibit, AIAA, Honolulu, HI.
Choi, Y.-H., Lee, T.-K., and Oh, S.-Y. (2008). “A line feature based SLAM with low grade range sensors using geometric constraints and active exploration for mobile robot.” Auton. Robots, 24(1), 13–27.
Davison, A., Nicholas, M., and Olivier, S. (2007). “MonoSLAM: Real-time single camera SLAM.” IEEE Trans. Pattern Anal. Mach. Intell., 29(6), 1052–1067.
Douglas, D., and Peucker, T. (1973). “Algorithms for the reduction of the number of points required to represent a digitized line or its caricature.” Cartographica: Int. J. Geograph. Inf. Geovisual,, 10(2), 112–122.
Jolliffe, I. T. (1986). Principal component analysis, Springer, New York.
Kim, H.-D., Seo, S.-W., Jang, I.-H., and Sim, K.-B. (2007). “SLAM of mobile robot in the indoor environment with distal magnetic compass and ultrasonic sensor.” Proc., Int. Conf. on Control, Automation and Systems (ICCAS), Seoul, Korea, 87–90.
Lee, J.-O., Kang, T., Lee, K.-H., Im, S., and Park, J. (2011). “Vision-based indoor localization for unmanned aerial vehicles.” J. Aerosp. Eng., 24(3), 373–377.
Lowe, D. G. (2004). “Distinctive image features from scale-invariant keypoints.” Int. J. Comput. Vis., 60(2), 91–110.
Lucas, B. D., and Kanade, T. (1981). “An iterative image registration technique with an application to stereo vision.” Proc., Int. Joint Conf. on Artificial Intelligence, Vancouver, Canada, 674–679.
Markus, A., Abraham, B., Ruijie, H., Samuel, P., and Nicholas, R. (2008). “Autonomous navigation and exploration of a quadrotor helicopter in GPS-denied indoor environments.” Proc., Robotics Science and Systems Conf., Institute of Robotics and Intelligent Systems, Zurich, Switzerland.
Mondragon, I. F., Campoy, P., Correa, J. F., and Mejias, L. (2007). “Visual model feature tracking for UAV control.” Proc., IEEE Int. Symp. on Intelligent Signal Processing, IEEE, Alcala de Henares, Spain, 1–6.
Munguia, R., and Grau, A. (2007). “Monocular SLAM for visual odometry.” Proc., IEEE Int. Symp. on Intelligent Signal Processing (WIPS), IEEE, Alcala de Henares, Spain, 1–6.
Pollefeys, M., Koch, R., and Gool, L. V. (1998). “Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters.” Proc., 6th Int. Conf. Computer Vision, IEEE, Bombay, India, 90–96.
Se, S., Lowe, D., and Little, J. (2002). “Mobile robot localization and mapping with uncertainty using scale-invariant visual landmarks.” Int. J. Robot. Res., 21(8), 735–758.
Shi, J., and Tomasi, C. (1994). “Good features to track.” Proc., IEEE Conf. on Computer Vision and Pattern Recognition, IEEE Computer Society Press, Seattle, WA, 593–600.
Sinha, S. N., Frahm, J., Pollefeys, M., and Genc, Y. (2006). “GPU-based video feature tracking and matching.” Workshop on Edge Computing Using New Commodity Architectures, DARPA, Chapel Hill, NC.
Snavely, N., Seitz, S. M., and Szeliski, R. (2006). “Photo tourism: Exploring photo collections in 3D.” ACM Trans. Graph., 25(3), 835–846.
Tomasi, C., and Kanade, T. (1991). “Detection and tracking of point features.” Tech. Rep. CMU-CS-91-132, Carnegie Mellon Univ., Pittsburgh.
Valavanis, K. P. (2007). “Design and control of a miniature quadrotor.” Advances in unmanned aerial vehicles, Springer, Dordrecht, Netherlands, 171–210.
Xu, L., Chen, W., Song, W., and Wang, J. (2008). “Multi-vision information fusion of a laser scanning system.” Proc., 6th IEEE Int. Conf. on Industrial Informatics (INDIN), IEEE, Daejeon, Korea, 46–50.
Zingg, S., Scaramuzza, D., Weiss, S., and Siegwart, R. (2010). “MAV navigation through indoor corridors using optical flow.” Proc., IEEE Int. Conf. on Robotics and Automation, IEEE, Anchorage, AK, 3361–3368.
Information & Authors
Information
Published In
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Mar 2, 2011
Accepted: Sep 8, 2011
Published online: Sep 10, 2011
Published in print: Oct 1, 2012
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.