赵立军, 孙立宁, 李瑞峰, 葛连正. 室内环境下同步定位与地图创建改进算法[J]. 机器人, 2009, 31(5): 438-444..
ZHAO Lijun, SUN Lining, LI Ruifeng, GE Lianzheng . On an Improved SLAM Algorithm in Indoor Environment. ROBOT, 2009, 31(5): 438-444..
Abstract:A new simultaneous localization and mapping(SLAM)algorithm based on the square root unscented Kalman filter(SRUKF)is proposed for indoor environments.This algorithm uses square root unscented particle filter for estimating the robot states in every iteration,meanwhile,introduces SRUKF to localize the estimated landmarks,and then updates the robot states and landmark information.The proposed algorithm is combined with the robot motion model and observation model of infrared tag in simulation and experiment,and the results show that the algorithm improves the accuracy and stability of the estimated robot state and landmarks in SLAM.
[1] Smith R C,Cheeseman P.On the representation and estimation of spatial uncertainty[J].The International Journal of Robotics Research,1987,5(4):56-68.
[2] Smith R C,Self M,Cheeseman P Estimating uncertain spatial relationships in robotics[M]//Autonomous Robot Vehicles.New York,USA:Springer-Verlag,1990:167-193.
[3] Dissanayake M W M G,Newman P,Clark S,et al.A solution to the simultaneous localization and map building(SLAM)problera[J].IEEE Transactions on Robotics and Automation,2001,17(3):229-241.
[4] Murphy K P.Bayesian map learning in dynamic environments[C]//Proceedings of the Annual Conference on Neural Information Processing Systems.Cambridge,MA,USA:MIT Press,2000:1015-1021.
[5] Montemerlo M,Thrun S,Koller D,et al.FastSLAM 2.0:An improved particle filtering algorithm for simultaneous localization and mapping that provably converges[C]//Proceedings of the International Conference on Artificial Intelligence.Acapulco,Mexico:UCAI,2003:1151-1156.
[6] Montemerio M,Thrun S,Koller D,et al.FastSLAM:A factored solution to the simultaneous localization and mapping problem[C]//Proceedings of the Nafional Conference on Artiflcial Intelligence.Cambridge,MA,USA:MIT Press,2002:593-598.
[7] Montemerlo M.FastSLAM:A Factored Solution to the Simultaneous Localization and Mapping Problem with Unknown Data Association[D].Pittsburgh,PA,USA:Carnegie Mellon University,2003.
[8] Wang X,Zhang H.A UPF-UKF framework for SLAM[C]//Proceedings of the IEEE International Conference on Robotics and Automation.Piscataway,NJ,USA:IEEE,2007:1664-1669.
[9] Kim C,Sakthivel R,Chung W K.Unscented FastSLAM:A robust algorithm for the simultaneous localization and mapping problem[C]//Proceedings of the IEEE International Conference on Robotics and Automation.Piscataway,NJ,USA:IEEE,2007:2439-2445.
[10] Julier S J.The sealed unscented transformation[C]//Proceedings of the American Control Conference.Piscataway,NJ,USA:IEEE,2002:4555-4559.
[11] Hahnei D,Thrun S,Wegbreit B,et al.Towards lazy data association in SLAM[C]//Proceodings of the International Symposium on Robotics Research.Berlin,Germany:Springer,2005:421-431.
[12] Julier S J,Uhlmann J K.A counter example to the theory of simultaneous localization and map building[C]//Proceedings of the IEEE Intemationai Conference on Robotics and Automation.Piscataway,NJ,USA:IEEE,2001:4238-4243.