SLAM算法在AUV中的应用进展

刘明雍; 赵 涛; 周良荣

doi:10.11993/j.issn.1673-1948.2010.01.009

SLAM算法在AUV中的应用进展

doi: 10.11993/j.issn.1673-1948.2010.01.009

西北工业大学航海学院,陕西西安,710072

基金项目: 新世纪优秀人才支持计划项目资助（NCET-06-0877)

详细信息

作者简介:
刘明雍（1971-) ，男，教授，博导，主要从事控制、制导与仿真方向的研究.

中图分类号: TJ630.33;TP24
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- 被引次数: 0
出版历程
- 收稿日期: 2008-03-09
- 修回日期: 2008-06-04
- 刊出日期: 2010-02-28

Application of Simultaneous Localization and Mapping to AUV

College of Marine Engineering, Northwestern Polytechnical University,Xi′an 710072,China

摘要

摘要: 同步定位与地图创建（SLAM）是水下航行器在全球范围内实现自主导航的一个基础且重要问题。首先介绍了SLAM算法在水下航行器应用的国内外最新进展，指出了SLAM算法所面临的问题，阐述了研究的环境描述、环境特征提取和不确定信息的描述等难点问题，并对SLAM算法的主要实现方式进行了归纳。最后结合水下航行器的特殊应用环境，探讨了未来SLAM算法的研究趋势和发展方向。
- 同步定位与地图创建（SLAM) /
- 自主水下航行器（AUV) /
- 环境特征提取 /
- 不确定信息
Abstract: Simultaneous localization and mapping (SLAM) is vital to worldwide autonomous navigation of autonomous underwater vehicle(AUV).We introduce the latest progress of SLAM algorithm for AUV both at home and abroad,with emphasis on SLAM algorithm in complicated underwater environment,and indicate the difficult problems in SLAM algorithm such as environment description,environment feature extraction,and uncertain information description.Moreover,we sum up some typical implementing methods of SLAM algorithm,and analyze the trends of SLAM algorithm research and development according to the special application environment of AUV.
- simultaneous localization and mapping(SLAM) /
- autonomous underwater vehicle(AUV) /
- environment feature extraction /
- uncertain information

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