Open Access
MATEC Web of Conferences
Volume 42, 2016
2015 The 3rd International Conference on Control, Mechatronics and Automation (ICCMA 2015)
Article Number 03008
Number of page(s) 6
Section Robot design and development
Published online 17 February 2016
  1. R. P. Mahler, Statistical multisource-multitarget information fusion. Artech House, Inc., 2007.
  2. G. Welch and G. Bishop, “An introduction to the kalman filter. 2006,” University of North Carolina: Chapel Hill, North Carolina, US.
  3. S. J. Julier and J. K. Uhlmann, “New extension of the kalman filter to nonlinear systems,” in AeroSense’97. International Society for Optics and Photonics, 1997, pp. 182–193.
  4. L. D. Stone, T. L. Corwin, and C. A. Barlow, “Bayesian multiple target tracking,” 1999.
  5. A. Doucet, N. De Freitas, and N. Gordon, An introduction to sequential Monte Carlo methods. Springer, 2001. [CrossRef]
  6. B. A. Berg, “Markov chain monte carlo simulations and their statistical analysis,” 2004.
  7. D. Crisan and A. Doucet, “A survey of convergence results on particle filtering methods for practitioners,” Signal Processing, IEEE Transactions on, vol. 50, no. 3, pp. 736–746, 2002. [CrossRef]
  8. R. Siegwart, I. R. Nourbakhsh, and D. Scaramuzza, Introduction to autonomous mobile robots. MIT press, 2011.
  9. B. Khaleghi, A. Khamis, F. O. Karray, and S. N. Razavi, “Multisensor data fusion: A review of the state-of-the-art,” Information Fusion, vol. 14, no. 1, pp. 28–44, 2013. [CrossRef]