Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In this paper an adaptive unscented Kalman filter based mixing filter is used to integrate kinematic satellite aided inertial navigation system with vision based measurements of five representative points on a runway in a modern receiver that incorporates carrier phase smoothing and ambiguity resolution. Using high resolution multiple stereo camera based measurements of five points on the runway, in addition to a set of typical pseudo-range estimates that can be obtained from a satellite navigation system such GPS or GNSS equipped with a carrier phase receiver, the feasibility of generating high precision estimates of the typical outputs from an inertial navigation system is demonstrated. The methodology may be developed as a stand-alone system or employed in conjunction with a traditional strapped down inertial navigation systems for purposes of initial alignment. Moreover the feasibility of employing adaptive mixing was explored as it facilitates the possibility of using the system for developing a vision based automatic landing controller.
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Tom
Strony
131--153
Opis fizyczny
Bibliogr. 26 poz., rys.
Twórcy
Bibliografia
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- [13] Malis E., Vision-based control invariant to camera intrinsic parameters: stability analysis and path tracking, IEEE International Conference on Robotics and Automation, Washington, D.C., USA, 2002.
- [14] Malis E., Chaumette F., Boudet, S., 2 1/2 d visual servoing, IEEE Trans. on Robotics and Automation, 1999, Vol. 15, No. 2, pp. 234-246.
- [15] Malis E., Chaumette F., Boudet S., 2 1/2 d visual servoing with respect to unknown objects through a new estimation scheme of camera displacement, International Journal of Computer Vision, 2000, Vol. 37, No. 1, pp. 79-97.
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- [17] Roumeliotis S., Johnson A., Montgomery J., Augmenting inertial navigation with image-based motion estimation, IEEE International Conference on Robotics and Automation (ICRA), p. 4326-33, Washington, D.C., USA, 2002.
- [18] Savage P., Strapdown inertial navigation integration algorithm design, part 1, Attitude algorithms, Journal of Guidance, Control and Dynamics, 1998, Vol. 21, No. 1, pp. 19-28.
- [19] Savage P., Strapdown inertial navigation integration algorithm design, part 2: Velocity and position algorithms, Journal of Guidance, Control and Dynamics, 1998, Vol. 21, No. 3, pp. 208-221.
- [20] Shakernia O., Ma Y., Koo T. J., Sastry S., Landing an Unmanned Air Vehicle: Vision Based Motion Estimation and Nonlinear Control, Asian Journal of Control, 1999, Vol. 1, No. 3, pp. 128-145.
- [21] Shang J., Shi Z., Vision-based Runway Recognition for UAV Autonomous Landing, IJCSNS International Journal of Computer Science and Network Security, 2007, Vol. 7, No. 3, pp. 112-117.
- [22] Sharp C. S., Shakernia O., Sastry S. S., A Vision System for Landing an Unmanned Aerial Vehicle, Proceedings of the IEEE, 2001.
- [23] Song Q., Qi J., Han J., An Adaptive UKF Algorithm and Its Application in Mobile Robot Control, ROBIO ’06, IEEE International Conference on Robotics and Biomimetics, Kunming, China, 2006, pp. 1117-1122.
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- [26] Wu A., Johnson E., Proctor A., Vision-aided inertial navigation for flight control, Proceedings of the AIAA Guidance, Navigation, and Control Conference, number AIAA 2005-5998, San Francisco, CA, 2005.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-66b3affe-b2ab-41b5-b451-f317dacb0d83