[5] Loo S Y, Amiri A J, Mashohor S et al. CNN-SVO: improving the mapping in semi-direct visual odometry using single-image depth prediction[C]. //2019 International Conference on Robotics and Automation (ICRA), May 20-24, 2019, Montreal, QC, Canada, 5218-5223(2019).
[6] Wang Y B, Huang S D. Motion segmentation based robust RGB-D SLAM[C]. //Proceeding of the 11th World Congress on Intelligent Control and Automation, June 29-July 4, 2014, Shenyang, China., 3122-3127(2014).
[8] Wang J, Wu X X, Guo B L. Robot path planning using improved particle swarm optimization[J]. Computer Engineering and Applications, 48, 240-244(2012).
[9] Li S D, Ding M Y, Cai C et al. Efficient path planning method based on genetic algorithm combining path network[C]. //2010 Fourth International Conference on Genetic and Evolutionary Computing, December 13-15, 2010, Shenzhen, China., 194-197(2010).
[10] Tao T, Huang Y L, Sun F C et al. Motion planning for SLAM based on frontier exploration[C]. //2007 International Conference on Mechatronics and Automation, August 5-8, 2007, Harbin, China., 2120-2125(2007).
[12] Mozos O M, Stachniss C, Burgard W. Supervised learning of places from range data using AdaBoost[C]. //Proceedings of the 2005 IEEE International Conference on Robotics and Automation, April 18-22, 2005, Barcelona, Spain., 1730-1735(2005).
[14] Freund Y, Schapire R E. A desicion-theoretic generalization of on-line learning and an application to boosting[M]. //Vitányi P. Computational learning theory. Lecture notes in computer science, 904, 23-37(1995).