2.624

2020影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

平方根容积Rao-Blackwillised粒子滤波SLAM算法

宋宇 李庆玲 康轶非 闫德立

宋宇, 李庆玲, 康轶非, 闫德立. 平方根容积Rao-Blackwillised粒子滤波SLAM算法. 自动化学报, 2014, 40(2): 357-367. doi: 10.3724/SP.J.1004.2014.00357
引用本文: 宋宇, 李庆玲, 康轶非, 闫德立. 平方根容积Rao-Blackwillised粒子滤波SLAM算法. 自动化学报, 2014, 40(2): 357-367. doi: 10.3724/SP.J.1004.2014.00357
SONG Yu, LI Qing-Ling, KANG Yi-Fei, YAN De-Li. SLAM with Square-root Cubature Rao-Blackwillised Particle Filter. ACTA AUTOMATICA SINICA, 2014, 40(2): 357-367. doi: 10.3724/SP.J.1004.2014.00357
Citation: SONG Yu, LI Qing-Ling, KANG Yi-Fei, YAN De-Li. SLAM with Square-root Cubature Rao-Blackwillised Particle Filter. ACTA AUTOMATICA SINICA, 2014, 40(2): 357-367. doi: 10.3724/SP.J.1004.2014.00357

平方根容积Rao-Blackwillised粒子滤波SLAM算法

doi: 10.3724/SP.J.1004.2014.00357
基金项目: 

国家自然科学基金(60905055,61005070);哈尔滨工业大学机器人技术与系统国家重点实验室开放基金(SKLRS-2009-ZD-04);中央高校基本科研业务费(2014JBM014)资助

详细信息
    作者简介:

    李庆玲 中国矿业大学(北京)机电与信息工程学院讲师.2009年在哈尔滨工业大学机器人技术与系统国家重点实验室获博士学位.主要研究方向为康复机器人系统. E-mail:qingling.li@ia.ac.cn

SLAM with Square-root Cubature Rao-Blackwillised Particle Filter

Funds: 

Supported by National Natural Science Foundation of China (60905055, 61005070), Open Function of State Key Laboratory of Robotics and System of Harbin Institute of Technology (SKLRS-2009-ZD-04), and Fundamental Research Funds for the Central Universities of China (2014JBM014)

  • 摘要: 面向大尺度环境中的移动机器人同时定位与地图构建(Simultaneous localization and mapping,SLAM)问题,提出平方根容积Rao-Blackwillised粒子滤波SLAM算法. 算法主要特点在于:1)采用容积律计算SLAM中的非线性函数高斯权重积分,达到减小SLAM非线性模型线性化误差、提高SLAM精度的目的;2)在SLAM中直接传播误差协方差矩阵的平方根因子,避免了耗费时间的协方差矩阵分解与重构过程,提高了SLAM计算效率. 通过仿真、实验将提出的SLAM算法与FastSLAM2.0、UFastSLAM两种算法进行对比,结果表明本文算法在SLAM性能上优于另两者.
  • [1] Durrant-Whyte H, Bailey T. Simultaneous localization and mapping: part I. IEEE Robotics and Automation Magazine, 2006, 13(2): 99-110
    [2] Bailey T, Durrant-Whyte H. Simultaneous localization and mapping: part Ⅱ. IEEE Robotics and Automation Magazine, 2006, 13(3): 108-117
    [3] Montemerlo M. FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem with Unknown Data Association[Ph.D. dissertation], Carnegie Mellon University, Pennsylvania, 2003
    [4] Grisetti G, Stachniss C, Burgard W. Improved techniques for grid mapping with Rao-Blackwellized particle filters. IEEE Transactions on Robotics, 2007, 23(1): 34-46
    [5] Sim R, Elinas P, Little J J. A study of the Rao-Blackwellised particle filter for efficient and accurate vision-based SLAM. International Journal of Computer Vision, 2007, 74(3): 303-318
    [6] Kim C, Sakthivel R, Chung W K. Unscented FastSLAM: a robust and efficient solution to the SLAM problem. IEEE Transactions on Robotics, 2008, 24(4): 808-820
    [7] Julier S J, Uhlmann J K. Unscented filtering and nonlinear estimation. Proceedings of the IEEE, 2004, 92(3): 401-422
    [8] Zhu Ji-Hua, Zheng Nan-Ning, Yuan Ze-Jian, Zhang Qiang. A SLAM algorithm based on central difference particle filter. Acta Automatica Sinica, 2010, 36(2): 249-257 (祝继华, 郑南宁, 袁泽剑, 张强. 基于中心差分粒子滤波的SLAM算法. 自动化学报, 2010, 36(2): 249-257)
    [9] Kim C, Kim H K, Chung W K. Exactly Rao-Blackwellized unscented particle filters for SLAM. In: Proceedings of the 2011 IEEE International Conference on Robotics and Automation. Shanghai, China: IEEE, 2011. 3589-3594
    [10] Song Y, Li Q L, Kang Y F, Song Y D. CFastSLAM: a new jacobian free solution to SLAM problem. In: Proceedings of the 2012 IEEE International Conference on Robotics and Automation. Saint Paul, USA: IEEE, 2012. 3063-3068
    [11] Arasaratnam I, Haykin S. Cubature Kalman filters. IEEE Transactions on Automatic Control, 2009, 54(6): 1254-1269
    [12] van der Merwe R, Wan E A. The square-root unscented kalman filter for state and parameter-estimation. In: Proceedings of the 2001 IEEE International Conference on Acoustic, Speech and Signal Processing. Salt Lake City, USA: IEEE, 2001. 3461-3464
    [13] Guivant J E, Nebot E M. Optimization of the simultaneous localization and map-building algorithm for real-time implementation. IEEE Transactions on Robotics and Automation, 2001, 17(3): 242-257
    [14] Huang S D, Wang Z, Dissanayake G. Sparse local submap joining filter for building large-scale maps. IEEE Transactions on Robotics, 2008, 24(5): 1121-1130
  • 加载中
计量
  • 文章访问数:  2364
  • HTML全文浏览量:  109
  • PDF下载量:  2215
  • 被引次数: 0
出版历程
  • 收稿日期:  2012-09-05
  • 修回日期:  2013-02-04
  • 刊出日期:  2014-02-20

目录

    /

    返回文章
    返回