Multi-robot Active Simultaneous Localization and Mapping Based on Local Submap Approach
YUAN Jing1, HUANG Ya-lou2, TAO Tong2, XI Bai-yu2
1. College of Information Technical Science, Nankai University, Tianjin 300071, China; 2. College of Software, Nankai University, Tianjin 300071, China
苑晶, 黄亚楼, 陶通, 习白羽. 基于局部子地图方法的多机器人主动同时定位与地图创建[J]. 机器人, 2009, 31(2): 97-103..
YUAN Jing, HUANG Ya-lou, TAO Tong, XI Bai-yu. Multi-robot Active Simultaneous Localization and Mapping Based on Local Submap Approach. ROBOT, 2009, 31(2): 97-103..
Abstract：The cooperative simultaneous localization and mapping(SLAM) finished in an active way by multiple robots in unknown environment is investigated.Local submap strategy is introduced in which each robot carries out map building in the local area around itself so that it can build local submap independent of other robots,then the SLAM problem in global environment can be decomposed into multiple sub-problems.The problem of active SLAM is converted into that of multiobjective optimization when each robot builds its local submap.The robot chooses the optimal control inputs so that the accuracy of localization and mapping,information gain and the cooperative motion will be synthetically optimized.Finally, all the submaps are fused into global map by extended Kalman filter(EKF).Simulation results prove the effectiveness of the prsented approach.
[1] Fenwick J W,Newman P M,leonard J J.Cooperative concurrent mapping and localization[A].Proceedings of the IEEE International Conference on Robotics and Automation[C].Piscataway,NJ,USA:IEEE,2002.1810～1817.
[2] Thrun S,Burgard W,Fox D.A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping[A].Proceedings of the IEEE International Conference on Robotics and Automation[C].Piscataway,NJ,USA:IEEE,2000.321～328.
[3] Thrun S,Liu Y E Multi-robot SLAM with sparse extended information filters[A].Springer Tracts in Advanced Robotics (vol.15)[M].Berlin,Germany:Springer,2003.254～266.
[4] Ko J,Stewart B,Fox D,et al.A practical,decision-theoretic approach to multi-robot mapping and exploration[A].Proceedings of the 1EEE/RSJ International Conference on Intelligent Robots and Systems[C].Piscataway,NJ,USA:IEEE,2003.3232～3238.
[5] Fox D.Distributed multi-robot exploration and mapping[A].Proceedings of the 2nd Canadian Conference on Computer and Robot Vision[C].Piscataway,NJ,USA:IEEE,2005.1325～1339.
[6] Williams S B.Efficient Solutions to Autonomous Mapping and Navigation Problems[D].Sydney,Australia:University of Sydney,2001.
[7] Williams S B,Dissanayake G,Durrant-Whyte H.Towards multi-vehicle simultaneous localisation and mapping[A].Proceedings of the IEEE International Conference on Robotics and Automation[C].Piscataway,NJ,USA:IEEE,2002.2743～2748.
[8] Dissanayake M W M G,Newman P,Clark S,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.
[9] Sim R,Elinas P,Griffin M,et al.Vision-based SLAM using the Rao-Blackwellised particle filter[DB/OL] ,http://www.cs.ubc.ca/～simra/publications/rur05_sim.pdf,2005.
[10] Zhang S,Xie L H,Adams M.An efficient data association approach to simultaneous localization and map building[A].Proceedings of the IEEE International Conference on Robotics and Automation[C].Piscataway,NJ,USA:IEEE,2004.854～859.
[11] Feder H J S,Leonard J J,Smith C M.Adaptive mobile robot navigation and mapping[J].The International Journal of Robotics Research,1999,18(7):650～668.
[12] Yamauchi B.A frontier-based approach for autonomous exploration[A].Proceedings,of the IEEE International Symposium on Computational Intelligence in Robotics and Automation[C].Los Alamitos,CA,USA:IEEE Computer Society,1997.146～151.
