大规模环境下基于图优化SLAM的图构建方法

被引:28
作者
王忠立 [1 ,2 ]
赵杰 [2 ]
蔡鹤皋 [2 ]
机构
[1] 北京交通大学电子信息工程学院
[2] 机器人技术与系统国家重点实验室(哈尔滨工业大学)
关键词
移动机器人; 同步定位与建图; 动态贝叶斯网络; 图建模; 数据关联;
D O I
暂无
中图分类号
TP242 [机器人];
学科分类号
1111 ;
摘要
分析总结了基于图优化同步定位和地图构建(SLAM)前端图构建过程的各种方法.对现有SLAM研究方法进行分类,指出基于Kalman滤波器、粒子滤波器、图优化方法的优缺点;重点介绍SLAM问题的3种图建模方法,即动态贝叶斯网络的图建模方法、基于因子图的建模方法、基于Markov随机场的建模方法;对图优化SLAM方法前端图构建的核心环节——帧间数据关联和环形闭合检测方法进行了分析;讨论了特征提取、特征匹配、运动估计、环形闭合检测等方面的最新研究成果.
引用
收藏
页码:75 / 85
页数:11
相关论文
共 16 条
  • [1] Efficient keyframe-based real-time camera tracking[J] . Zilong Dong,Guofeng Zhang,Jiaya Jia,Hujun Bao.Computer Vision and Image Understanding . 2014
  • [2] Map Building Fusing Acoustic and Visual Information using Autonomous Underwater Vehicles
    Kunz, Clayton
    Singh, Hanumant
    [J]. JOURNAL OF FIELD ROBOTICS, 2013, 30 (05) : 763 - 783
  • [3] 1‐Point RANSAC for extended Kalman filtering: Application to real‐time structure from motion and visual odometry[J] . JavierCivera,Oscar G.Grasa,Andrew J.Davison,J. M. M.Montiel.J. Field Robotics . 2010 (5)
  • [4] Speeded-Up Robust Features (SURF)[J] . Herbert Bay,Andreas Ess,Tinne Tuytelaars,Luc Van Gool.Computer Vision and Image Understanding . 2007 (3)
  • [5] A review of recent range image registration methods with accuracy evaluation[J] . Joaquim Salvi,Carles Matabosch,David Fofi,Josep Forest.Image and Vision Computing . 2006 (5)
  • [6] Visual odometry for ground vehicle applications
    Nister, David
    Naroditsky, Oleg
    Bergen, James
    [J]. JOURNAL OF FIELD ROBOTICS, 2006, 23 (01) : 3 - 20
  • [7] Preemptive RANSAC for live structure and motion estimation
    Nistér, D
    [J]. MACHINE VISION AND APPLICATIONS, 2005, 16 (05) : 321 - 329
  • [8] Scale & affine invariant interest point detectors
    Mikolajczyk, K
    Schmid, C
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 2004, 60 (01) : 63 - 86
  • [9] Robust registration of 2D and 3D point sets[J] . Andrew W Fitzgibbon.Image and Vision Computing . 2003 (13)
  • [10] Factorization with Uncertainty[J] . P. Anandan,Michal Irani.International Journal of Computer Vision . 2002 (2)