References
- Arasaratnam, I., & Haykin, S. (2009). Cubature Kalman filters. IEEE Transactions on Automatic Control, 54(6), 1254–1269. doi:10.1109/TAC.2009.2019800
- Bailey, T. (n.d.). SLAM simulations. Retrieved from http://www-personal. acfr.usyd.edu.au/tbailey/software/slam_simulations.htm.
- Chang, L., Hu, B., Li, A., & Qin, F. (2013). Transformed unscented Kalman filter. IEEE Transactions on Automatic Control, 58(1), 252–257. doi:10.1109/TAC.2012.2204830
- Chee, S.L., Nagappa, S., Palomeras, N., Clark, D.E., & Salvi, J. (2014). SLAM with SC-PHD filters: An underwater vehicle application. IEEE Robotics & Automation Magazine, 21(2), 38–45. doi:10.1109/MRA.2014.2310132
- Dissanayake, M.W.M.G., Newman, P., Clark, S., Durrant-Whyte, H.F., & Csorba, M. (2001). A solution to the simultaneous localization and map building (SLAM) problem. IEEE Transactions on Robotics and Automation, 17(3), 229–241. doi:10.1109/70.938381
- Doucet, A., De Freitas, N., Gordon, N. & Smith, A. (2001). Sequential Monte Carlo methods in practice. New York, NY: Springer-Verlag.
- Durrant-Whyte, H., & Bailey, T. (2006). Simultaneous localization and mapping: Part I. IEEE Robotics & Automation Magazine, 13(2), 99–110. doi:10.1109/MRA.2006.1638022
- Fox, D. (2003). Adapting the sample size in particle filters through KLD-sampling. International Journal of Robotics Research, 22(12), 985–1003. doi:10.1177/0278364903022012001
- Ghadiok, V., Goldin, J., & Wei, R. (2011). Autonomous indoor aerial gripping using a quadrotor. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (pp. 4645–4651). San Francisco, CA.
- Havangi, R., Nekoui, M., Teshnehlab, M. & Taghirad, H. (2014). A SLAM based on auxiliary marginalised particle filter and differential evolution. International Journal of Systems Science, 45(9), 1913–1926. doi:10.1080/00207721.2012.759299
- Havangi, R., Taghirad, H., Nekoui, M. & Teshnehlab, M. (2014). A square root unscented FastSLAM with improved proposal distribution and resampling. IEEE Transactions on Industrial Electronics, 61(5), 2334–2345. doi:10.1109/TIE.2013.2270211
- Julier, S.J., & Uhlmann, J.K. (2004). Unscented filtering and nonlinear estimation. Proceedings of the IEEE, 92(3), 401–422. doi:10.1109/JPROC.2003.823141
- Kim, C., Sakthivel, R., & Chung, W.K. (2008). Unscented FastSLAM: A robust and efficient solution to the SLAM problem. IEEE Transactions on Robotics, 24(4), 808–820. doi:10.1109/TRO.2008.924946
- Li, T., Sun, S., & Sattar, T.P. (2013). Adapting sample size in particle filters through KLD-resampling. Electronics Letters, 49(12), 740–742. doi:10.1049/el.2013.0233
- Montemerlo, M., Thrun, S., Koller, D., & Wegbreit, B. (2002). FastSLAM: A factored solution to the simultaneous localization and mapping problem. In Proceedings of the National Conference on Artificial Intelligence (pp. 593–598). Edmonton.
- Montemerlo, M., & Thrun, S. (2003). Simultaneous localization and mapping with unknown data association using FastSLAM. In Proceedings of the IEEE International Conference on Robotics and Automation (pp.1985–1991). Taipei.
- Murphy, K.P. (1999). Bayesian map learning in dynamic environments. In Proceedings of the Advances in Neural Information Processing Systems (pp. 1015–1021). Denver, CO.
- Nebot, E. (n.d.). Victoria Park dataset. Retrieved from http://www-personal. acfr.usyd.edu.au/nebot/dataset.htm.
- Song, Y., Li, Q., Kang, Y., & Song, Y. (2012). CFastSLAM: A new Jacobian free solution to SLAM problem. In Proceedings of the IEEE International Conference on Robotics and Automation (pp. 3063–3068). Saint Paul, MN.
- Ulas, C., & Temeltas, H. (2013). Feature-based 3D outdoor slam with local filters. International Journal of Robotics and Automation, 28(3), 226–233. doi:10.2316/Journal.206.2013.3.206-3792
- Zhu, J.H., Zheng, N.N., Yuan, Z.J., & Du, S.Y. (2011). Adaptive SLAM algorithm with sampling based on state uncertainty. Electronics Letters, 47(4), 284–286. doi:10.1049/el.2010.3476