精确稀疏扩展信息滤波的多机器人SLAM研究
PDF下载 (317)明钊光,石守东 *,王 刚.精确稀疏扩展信息滤波的多机器人SLAM研究[J].宁波大学学报(理工版),2014,27(04):42-46.DOI:
MING Zhao-guang,SHI Shou-dong *,WANG Gang.Multi-robot SLAM with Exactly Sparse Extended Information Filtering[J].Journal of Ningbo University(Natural Science & Engineering Edition),2014,27(04):42-46.DOI:
| Title: | Multi-robot SLAM with Exactly Sparse Extended Information Filtering |
| 作者: | 明钊光, 石守东 *, 王 刚 |
| Author(s): | MING Zhao-guang, SHI Shou-dong *, WANG Gang |
| 关键词: | 多机器人; 精确稀疏扩展信息滤波; 重定位 |
| Keywords: | SLAM; Multi-robot; exactly sparse extended information filters; relocalization |
| 分类号: | TP242.6 |
| 文献标识码: | A |
| 摘要: | 在机器人同时定位与地图创建(SLAM)问题中, 多机器人SLAM成为目前机器人学中的研究热点. 因此, 基于精确稀疏扩展信息滤波算法(ESEIF)的多机器人SLAM问题, 根据多机器人的运动模型和观测模型分别对多机器人位姿估计及环境特征点进行观测, 并依据阈值划分观测特征点, 以完成机器人的观测更新, 同时边缘化机器人位姿并进行重定位. 实验仿真数据表明: 多机器人的位姿精度良好, 观测更新阶段时间基本上恒定, 与地图特征点数量无关, 体现了ESEIF算法在研究多机器人SLAM问题的有效性. |
| Abstract: | In the robot simultaneous localization and mapping (SLAM) problem, the Multi-robot SLAM has drawn much attention recently in robotics. This paper investigates the Multi-robot SLAM problem in using exactly sparse extended information filters algorithm (ESEIF): Based on both the multi-robot motion model and observation model, the multi-robot pose is estimated and the environment features are observed. The threshold is set for partitioning and updating the observed features, and marginalizing the robot pose followed by relocating the robot. The simulation shows that the robots pose can be accurately estimated, and observation can be updated in a constant time fashion irrespective of the number of features in the map. |
| 参考文献 /References: | [1] Thrun S, Liu Y, Koller D, et al. Simultaneous localization and mapping with sparse extended information filters[J]. International Journal of Robotics Research, 2004, 23(7/8): 693-716. [2] Walter M, Eustice R, Leonard J. Exactly sparse extended information filter for feature-based SLAM[J]. The International Journal of Robotics Research. 2007, 26(4): 335-359. [3] Walter M, Eustice R, Leonard J. Sparse extended infor- mation filters: Insights into sparsification[C]. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems , Edmonton, 2005:3281-3288. [4] Walter M. Sparse Bayesian information filters for localization and mapping[D]. United States, Woods Hole: The Woods Hole Oceanographic Institution, 2008. [5] Thrun S, Koller D, Ghahramani Z, et al. Simultaneous mapping and localization with sparse extended infor- mation ?lters: Theory and Initial Results[C]. Proceedings of the Fifth International Workshop on Algorithmic Foundations of Robotics, Nice, France, 2002. [6] 郭剑辉, 赵春霞, 石杏喜. 稀疏扩展信息滤波SLAM 算法的稀疏规则研究[J].系统仿真学报, 2008, 20(24): 6673-6677. [7] 郭剑辉, 赵春霞. 一种改进的稀疏扩展信息滤波SLAM算法[J]. 模式识别与人工智能, 2009, 22(2):263-269. [8] Smith R, Self M, Cheeseman P. Estimating uncertain spatial relationships in robotics[J]. Uncertainty in Artificial Intelligence, 1986(2):267-288. [9] 徐斌斌, 石守东, 王小波. 基于扩展信息滤波的多机器人SLAM研究[J]. 宁波大学学报: 理工版, 2011, 24(1): 38-41. |
| 备注/Memo: | 收稿日期: 2013-01-10. 宁波大学学报（理工版）网址: http://journallg.nbu.edu.cn/基金项目: 浙江省教育厅科研项目（Y201121251）; 宁波市自然科学基金（2012A610008）.第一作者: 明钊光（1988－）, 男, 湖北黄石人, 在读硕士研究生, 主要研究方向: 多机器人的导航定位. E-mail: mingzhg@163.com*通信作者: 石守东（1964－）, 男, 浙江宁海人, 副教授, 主要研究方向: 计算机及人工智能. E-mail: shishoudong@nbu.edu.cn 宁波大学学报（理工版）网址：http://journallg.nbu.edu.cn/ |
