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《Chinese High Technology Letters》 2008-04
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An improved FastSLAM algorithm for mobile robots'self-navigation in unknown large-scale environments

Guo Lijin~(* **) Wang Huaxiang~(**) Meng Qinghao~(**) Zeng Ming~(**) Qiu Yanan~(**)(* School of Computer Technology and Automation,Tianjin Polytechnic University,Tianjin 300160)(** School of Electric Engineering and Automation,Tianjin University,Tianjin 300072)  
To solve the data association problem of the fast simultaneous location and mapping (FastSLAM) algorithm in un- known large-scale environments for mobile robots,the paper adopts a data association solution for FastSLAM algorithm in unknown large-scale environments (uncertain data association) by using the united technology of per-particle maximum likelihood and negative information approach.The improved algorithm uses the per-particle maximum likelihood approach to avoid the motion noise that has influence on the accuracy of the latter data association and the aim-lost phenomnen ap- pearing.It also uses the negative information method to avoid the erroneous landmarks added in the maps.Simulation re- sults show that the improved FastSLAM solves the data association and improves the performance of localization and map- ping greatly in the unknown large-scale environments.
【Fund】: 国家自然科学基金(60475028);; 天津市高等学校科技发展基金(2006ba54)资助项目
【CateGory Index】: TP242
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