Map management system for cv-SLAM

This paper present a map management system for ceiling vision (cv)-SLAM where a map is comprised of line landmarks on the ceiling. Since the size of a map, which is the number of landmarks, is related to computational and memorial cost, it should be managed in an appropriate size. For this purpose, the binary Bayes filter is utilized to estimate the probability of existence of a landmark. We demonstrate the system in the real world experiment to prove its performance.

[1]  Se-Young Oh,et al.  Grid-Based Visual SLAM in Complex Environments , 2007, J. Intell. Robotic Syst..

[2]  Se-Young Oh,et al.  Grid-based Visual SLAM in Complex Environment , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Ba-Ngu Vo,et al.  A Random-Finite-Set Approach to Bayesian SLAM , 2011, IEEE Transactions on Robotics.

[4]  Wan Kyun Chung,et al.  Effective Maximum Likelihood Grid Map With Conflict Evaluation Filter Using Sonar Sensors , 2009, IEEE Transactions on Robotics.

[5]  Euntai Kim,et al.  CV-SLAM using ceiling boundary , 2010, 2010 5th IEEE Conference on Industrial Electronics and Applications.

[6]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[7]  Frank Dellaert,et al.  Probabilistic structure matching for visual SLAM with a multi-camera rig , 2010, Comput. Vis. Image Underst..