Robust Landmark Estimation and Unscented Particle Sampling for SLAM in Dynamic Outdoor Environment
Atsushi Sakai, Teppei Saitoh, and Yoji Kuroda
Department of Mechanical Engineering, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan
-  S. Thrun, W. Burgard, and D. Fox, “Probabilistic Robotics,” MIT Press, 2005.
-  H. Durrant-Whyte and T. Bailey, “Simultaneous localization and mapping: part I,” IEEE Robotics & Automation Magazine, Vol.13, No.2, pp. 99-110, 2006.
-  T. Bailey and H. Durrant-Whyte, “Simultaneous localization and mapping (SLAM): part II,” Robotics & Automation Magazine, IEEE, Vol.13, No.3, pp. 108-117, 2006.
-  U. Freseand and G. Hirzinger, “Simultaneous localization and mapping-a discussion,” In Proc. of the Int. Conf. on Artificial Intelligence (IJCAI), 2001.
-  G. Dissanayake, P. Newman, S. Clark, H. F. Durrant-Whyte, and M. Csorba, “A solution to the simultaneous localisation and map building (SLAM) problem,” IEEE Trans. of Robotics and Automation, 2001.
-  D. M. Cole and P. M. Newman, “Using Laser Range Data for 3D SLAM in Outdoor Environments,” In Proc. of the IEEE Inter. Conf. on Robotics and Automation (ICRA ’06), Orlando, Florida, U.S.A., May 2006.
-  M. Kaess, A. Ranganathan, and F. Dellaert, “iSAM: Fast incremental smoothing and mapping with efficient data association,” in Proc. IEEE Int. Conf. Robot. Autom. (ICRA 2007), Roma, Italy, Apr. 10-14, pp. 1670-1677, 2007.
-  S. Thrun, D. Koller, Z. Ghahramani, H. Durrant-Whyte, and A. Y. Ng., “Simultaneous mapping and localization with sparse extended information filters,” In Proc. of WAFR, 2002.
-  J. Folkesson and H. Christensen, “Graphical SLAM for outdoor applications,” J. Field Robot., Vol.23, No.1, pp. 51-70, 705, 2006.
-  S. Thrun and M. Montemerlo, “The graphslam algorithm with applications to large-scale mapping of urban structures,” IJRR, Vol.25.
-  C. Kim, R. Sakthivel, and W. K. Chung, “Unscented FastSLAM: A robust algorithm for the simultaneous localization and mapping problem,” in Proc. IEEE Int. Conf. Robot. Autom., pp. 2439-2445, 2007.
-  K. Konolige and M. Agrawal, “Frameslam: From bundle adjustment to real-time visual mapping,” IEEE Trans. on Robotics, Vol.24, No.5, pp. 1066-1077, 2008.
-  T. D. Barfoot, “Online visual motion estimation using FastSLAM with SIFT features,” Edmonton, Alberta, August, pp. 3076-3082, 2005.
-  A. Diosi, G. Taylor, and L. Kleeman, “Interactive SLAM using laser and advanced sonar,” In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA ’05), Barcelona, Spain, April 2005.
-  M. Montemerlo, S. Thrun, “Simultaneous localization and mapping with unknown data association using FastSLAM,” Proc. ICRA, 2003.
-  J. Niento, J. Guivant, E. Nebot, and S. Thrun, “Real time data association in FastSLAM,” In Proc. of the IEEE Int. Conf. on Robotics and Automation, 2003.
-  M. Montemerlo, S. Thrun D. Koller, and B. Wegbreit, “FastSLAM 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges,” In Proc. of the Int. Conf. on Articial Intelligence (IJCAI), 2003.
-  M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit, “Fast-SLAM: A factored solution to the simultaneous localization andmapping problem,” Proc. AAAI, 2002.
-  S. J. Julier, J. K. Uhlmann, and H. F. Durrant-Whyte, “A new approach for filtering nonlinear systems,” in Proc. Amer. Contr. Conf., Seattle, WA, June, pp. 1628-1632, 1995.
-  R. Merwe and E. Wan, “Sigma-point Kalman filters for probabilistic inference in dynamic state-space models,” In Proc. Workshop on Advances in Machine Learning, Montreal, Canada, June 2003.
-  R. Merwe, A. Doucet, N. Freitas, and E. Wan, “The Unscented Particle Filter,” Technical Report CUED/F-INFENG/TR 380, Cambridge University Engineering Department, 2000.
-  S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for on-line non-linear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process., Vol.50, No.2, pp. 174-189, 2002.
-  G. Welch and G. Bishop, “An Introduction to the Kalman Filter,” TR-95-041, Dept. of Computer Science, Univ. of North Carolina, 2001.
-  D. Avitzour, “A maximum likelihood approach to data association,” IEEE Trans. on Aerospace and Electronics Systems, Vol.28, No.2, Apr., pp. 560-565, 1992.
-  MATLAB SLAM simulators by Tim Bailey
-  New Technology Foundation, “Tsukuba Challenge: Real World Robot Challenge [WWW page],”
http://www.robomedia.org/challenge/ (in Japanese)
-  Hokuyo Automatic Co., Ltd.
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