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Extended Kalman Filtering for Satellite Orbital Attitude Estimation Based on Gibbs Vector

Yurong Lin

Year
2004
Citations
7

Abstract

References 1Latombe, J.-C., “Motion Planning: A Journey of Robots, Molecules, Digital Actors, and Other Artifacts,” International Journal of Robotics Research, Vol. 18, No. 11, 1999, pp. 1119–1128. 2Bertsekas, D. P., Dynamic Programming and Optimal Control, 2nd ed., Vol. 1, Athena Scientific, Belmont, MA, 2001, Chap. 1, pp. 18–34. 3Sundar, S., and Shiller, Z., “Optimal Obstacle Avoidance Based on the Hamilton–Jacobi–Bellman Equation,” IEEE Transactions on Automatic Control, Vol. 13, No. 2, 1997, pp. 305–310. 4LaValle, S. M., and Kuffner, J. J., “Randomized Kinodynamic Planning,” International Journal of Robotics Research, Vol. 20, No. 5, 2001, pp. 378–400. 5Frazzoli, E., Daleh, M. A., and Feron, E., “Real-Time Motion Planning for Agile Autonomous Vehicles,” Journal of Guidance, Control, and Dynamics, Vol. 25, No. 1, 2002, pp. 116–129. 6Cerven, W. T., “Efficient Hierarchical Global Motion Planning for Autonomous Vehicles,” Ph.D. Dissertation, Dept. of Aerospace Engineering, Univ. of Illinois at Urbana–Champaign, Urbana, IL, Oct. 2003.

Keywords

Motion planningArtificial intelligenceRoboticsKalman filterObstacle avoidanceComputer scienceSatelliteExtended Kalman filterAerospaceAgile software development

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