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Hand gesture recognition based on free-form contours and probabilistic inference

References Arulampalam, M. S., Maskell, S. and Gordon, N. (2002). A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE Transactions on Signal Processing   50 (2): 174-188. Baum, L., Petrie, T., Soules, G. and Weiss, N. (1970). A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains, Annal Mathematics Statistics   41 (1): 164-171. Emambakhsh, M., Ebrahimnezhad, H. and Sedaaghi, M. H. (2010

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Mode set focused hybrid estimation

Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans 4 (5): 917-931. de Freitas, N. (2002). Rao-Blackwellised particle filtering for fault diagnosis, Proceedings of the IEEE Aerospace Conference 2002, Big Sky, MT, USA , Vol. 4, pp. 1767-1772. Dearden, R. and Clancy, D. (2002). Particle filters for real-time fault detection in planetary rovers, 13th International Workshop on Principles of Diagnosis, DX02, Semmering, Austria , pp. 1-6. Georges, J.-P., Theilliol, D., Cocquempot, V., Ponsart, J.-C. and Aubrun, C. (2011

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Transient Flow in Gas Networks: Traveling waves

. Liu, M., Zang, S. and Zhou, D. (2005). Fast leak detection and location of gas pipelines based on an adaptive particle filter, International Journal of Applied Mathematics and Computer Science 15(4): 541-550. Mugnolo, D. and Rault, J.-F. (2014). Construction of exact travelling waves for the Benjamin-Bona-Mahony equation on networks, Bulletin of the Belgian Mathematical Society Simon Stevin 21(3): 415-436. Osiadacz, A. (1984). Simulation of transient gas flows in networks, International Journal for Numerical Methods in Fluids 4(1): 13

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Simultaneous localization and mapping: A feature-based probabilistic approach

-the-fly localization: Precision and reliability for applications, Robotics and Autonomous Systems   34 (2-3): 131-143. Arulampalam, M. S., Maskell, S., Gordon, N. and Clapp, T. (2002). A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE Transactions on Signal Processing   50 (2): 174-187. Austin, D. and Jensfelt, P. (2000). Using multiple Gaussian hypotheses to represent probability distributions for mobile robot localization, Proceedings of the IEEE International Conference on Robotics and

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Model–Based Techniques for Virtual Sensing of Longitudinal Flight Parameters

References Arulampalam, S., Maskell, S. and Gordon, N. (2002). A tutorial on particle filters for on-line non-linear/non-Gaussian Bayesian tracking, IEEE Transactions on Signal Processing 50(2): 174-188. Boiffier, J.-L. (1998). The Dynamics of Flight: The Equations, John Wiley & Sons, Chichester. Bucharles, A., Cumer, C., Hardier, G., Jacquier, B., Janot, A., Le Moing, T., Seren, C., Toussaint, C. and Vacher, P. (2012). An overview of relevant issues for aircraft model identification, ONERA, AerospaceLab Journal

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An Ant–Based Filtering Random–Finite–Set Approach to Simultaneous Localization and Mapping

, Boston, MA. Michael, M., Sebastian, T., Daphne, K. and Ben, W. (2003). FastSLAM 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges, Proceedings of the 6th International Joint Conference on Artificial Intelligence, Acapulco, Mexico, pp. 1151-1156. Montemerlo, M., Thrun, S., Koller, D. and Wegbreit, B. (2002). FastSLAM: A factored solution to the simultaneous localization and mapping problem, Proceedings of the 8th National Conference on Artificial Intelligence, Edmonton, Alberta

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Straight-lines modelling using planar information for monocular SLAM

-Carranza, J. and Calway, A. (2009). Efficiently increasing map density in visual SLAM using planar features with adaptive measurements, British Machine Vision Conference (BMVC), London, UK , pp. 1-11. Marzorati, D., Matteucci, M., Migliori, D. and Sorrenti, D. (2009). On the use of inverse scaling in monocular SLAM, IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan , pp. 2030-2036. Moreno, F., Blanco, J. and Gonzalez, J. (2009). Stereo vision specific models for particle filter-based SLAM

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Simultaneous State and Parameter Estimation Based Actuator Fault Detection and Diagnosis for an Unmanned Helicopter

Control 18(8): 753-768. Kotecha, J. and Djuric, P. (2003). Gaussian particle filtering, IEEE Transactions on Signal Processing 51(10): 2592-2601. Qi, J., Han, J. and Wu, Z. (2008). Rotorcraft UAV actuator failure estimation with KF-based adaptive UKF algorithm, Proceedings of the American Control Conference, Seattle, WA, USA, pp. 1618-1623. Qi, J., Jiang, Z., Zhao, X. and Han, J. (2007). Adaptive UKF and its application in fault tolerant control of rotorcraft UAV, Proceedings of the AIAA Guidance, Navigation, and Control

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