[1] [1] Dissanayake, M W M G, et al., A solution to the simultaneous localization and map building (SLAM) problem[J]. IEEE Transactions on Robotics and Automation, 2001, 17(3): 229-241.

[2] [2] Ayache N, O D Faugeras. Maintaining representations of the environment of a mobile robot[J]. IEEE Transactions on Robotics and Automation, 2011, 5(6): 804-819.

[3] [3] Balasuriya, B L E A, et al. Outdoor robot navigation using gmapping based SLAM algorithm[C]//2016 Moratuwa Engineering Research Conference (MERCon), 2016.

[4] [4] Chen X, et al. Robust SLAM system based on monocular vision and LiDAR for robotic urban search and rescue[C]//2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), 2017.

[5] [5] Choi J. Hybrid map-based SLAM using a velodyne laser scanner[C]//17th International IEEE Conference on Intelligent Transportation Systems (ITSC), 2014.

[6] [6] Densmore J D, K G Thompson, T J Urbatsch. A hybrid transport-diffusion monte carlo method for frequency-dependent radiative-transfer simulations[J]. Journal of Computational Physics, 2012, 231(20): 6924-6934.

[7] [7] Fang H, et al. Ground-texture-based localization for intelligent vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2009, 10(3): 463-468.

[8] [8] Grisetti G, C Stachniss, W Burgard. Improved techniques for grid mapping with rao-blackwellized particle filters[J]. IEEE Transactions on Robotics, 2007, 23(1): 34-46.

[9] [9] Konolige K, et al. Efficient sparse pose adjustment for 2D mapping[C]//2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010.

[10] [10] Hess W, et al. Real-time loop closure in 2D LIDAR SLAM[C]//2016 IEEE International Conference on Robotics and Automation (ICRA), 2016.

[11] [11] Huang L. Review on LiDAR-based SLAM techniques[C]//2021 International Conference on Signal Processing and Machine Learning (CONF-SPML), 2021.