An Active Loop Closure Fast SLAM Method Base on Topology – Section Lines Cascading Map

Abstract:

Aim to the loop closure problems of mobile robots SLAM, a building mix cascading map approach base on topology-line segment feature is presented, and also an active loop closure Fast SLAM approach is proposed by using segments types of the section lines to form active loop closure tactics. According to topology nodes‘s relationship detect loop closure, and use a reverse movement model for optimization and modification to improve the accuracy and map consistency of robot’s localization. Experiment results show that the approach can well detect loop closure and reduce accumulated errors, and the robot’s localization accuracy and map consistency is remarkably improved.

• Periodical: Applied Mechanics and Materials (Volume 590)
• Pages: 470-477
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.590.470
• Online since: June 2014
• Authors: Guo Liang Zhang*, Jun Xu, Yi Jie Sun, Er Liang Yao
• Keywords: Active Loop Closure, Cascading Map, Llines Feature, Robot, Simultaneous Localization, Simultaneous Mapping

References

[1] Shen Lincheng, Xu Xin, Zhu Huayong, et al. The mobile autonomous robot control theory and technology [M]. Beijing: Science Press, 2011. 248-270.

[2] Cai Zixing, he Hanagan, Chen Hong. The unknown environment mobile robot navigation control problems [J]. Control and decision, 2002, 17 ( 4): 385-390.

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

DOI: 10.1109/70.938381

[4] Spero D J, Jarvis R A. A review of robotic SLAM: MECSE-4-2007[R]. Clayton: Monash University, (2007).

[5] Durrant-Whyte H, Bailey T. Simultaneous Localization and Mapping ( SLAM ): Part I [J]. IEEE Robotics and Automation Magazine, 2006, 13 ( 2): 99-107.

DOI: 10.1109/mra.2006.1678144

[6] Ji Xiucai. Robot simultaneous localization and mapping data association problem research [D]. Changsha: National University of Defense Technology, (2008).

[7] Gutmann J S, Burgard W, Fox D, et al. Experimental comparison of localization methods. Proceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 2 ( of 3 ), Oct 13-17 1998. Victoria, Can: IEEE Press, Piscataway, NJ, USA, 1998. 736-743.

DOI: 10.1109/iros.1998.727280

[8] Haris B, Panos T. Closing Multiple Loops while Mapping Features in Cyclic Environments. Proceedings of the 2003 IEEE/RSJ Intl. Conference on Intelligent Robots and Systems. Las Vegas, Nevada: IEEE Press, 2003 717-722.

DOI: 10.1109/iros.2003.1250714

[9] Tomatis N, Nourbakhsh I, Siegwart R. Hybrid simultaneous localization and map building: Closing the loop with multi-hypotheses tracking. 2002 IEEE International Conference on Robotics adn Automation, May 11-15 2002. Washington, DC, United States: IEEE Press, 2002 2749-2754.

DOI: 10.1109/robot.2002.1013648

[10] Huang Qingcheng, Hong Bing melting, Li Maohai, et al. Based on active closure constraints of mobile robot simultaneous localization and mapping [J]. Computer research and development. ISSN1000-1239 / CN11-1777 / T P44 (4) : 636-642200.

DOI: 10.1360/crad20070513

[11] Cerqueira J J E Palhares AGB, Madrid M K. A simple adaptive back-propagation algorithm for multilayered feedforward perceptrons [A]. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics[C]. Piscataway, USA: NJ, IEEE. 2002. 590～ 595.

DOI: 10.1109/icsmc.2002.1176108

[12] Arras K O, Tomatis N, Jensen B T, et al. Multisensor on-the-fly localization: Precision and reliability for applications [J]. Robotics and Autonomous Systems, 2001, 34 ( 2/3 ): 131-143.

DOI: 10.1016/s0921-8890(00)00117-2

[13] J. Castellanos and J. Tado' os. Laser-based Segmentation and Localization for a Mobile Robot. In Robotics and Manufacturing: Recent Trends in Research and Applications, Volume 6 ASME Press, (1996).

[14] T. Einsele. Real-Time Self-Localization in Unknown Indoor Environments using a Panorama Laser Range Finder. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 697 - 702, (1997).

DOI: 10.1109/iros.1997.655087

[15] G. A. Borges and M. -J. Aldon. Line Extraction in 2D Range Images for Mobile Robotics. Journal of Intelligent and Robotic Systems, 40: 267 - 297, (2004).

DOI: 10.1023/b:jint.0000038945.55712.65

[16] Ding Shuaihua. Based on local sub-map matching SLAM method [D]. Shanghai: Fudan University, (2009).

[17] WuTao, SunFengChi, YuanJing, et al. Based on line segment feature indoor environment active SLAM approach [J]. robot. 2009, 31 ( 2 ): 166-170.

[18] Martinelli A, Tomatis N, Siegwart R. Some Results on SLAM and the Closing the Loop Problem. IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton, Canada: 2005 2917-2922.

DOI: 10.1109/iros.2005.1545003

[19] Lu F, Milios E. Globally consistent range scan alignment for environment mapping. Autonomous Robots. 1997, 4: 333-349.