vslam: 扫盲之旅

蔚落 2022-06-17 08:11 166阅读 0赞

ICCV研讨会：实时SLAM的未来以及深度学习与SLAM的比较: http://blog.csdn.net/qq\_18661939/article/details/51919329

The Future of Real-time SLAM\[ZZ\]: https://zhuanlan.zhihu.com/p/21738966

SLAM 开发学习资源与经验分享：https://github.com/GeekLiB/Lee-SLAM-source?utm\_source=tuicool&utm\_medium=referral

## 目录 ##

*  [入门][Link 1]
 *  [基础][Link 2]
 *  [进阶][Link 3]
 *  [优秀文章][Link 4]
 *  [技术博客][Link 5]
 *  [网站与研究组织][Link 6]
 *  [书籍与资料][Link 7]
 *  [SLAM 方案][SLAM]
 *  [优秀案例][Link 8]
 *  [泡泡机器人专栏公开课][Link 9]

## 入门 ##

[视觉SLAM的基础知识-高翔][SLAM_-](高翔博士)-----视频，吐血推荐

[关于slam][slam]

[SLAM简介][SLAM 1]

[SLAM第一篇：基础知识][SLAM 2]

[SLAM\_介绍以及浅析][SLAM 3]

[SLAM的前世今生 终于有人说清楚了][SLAM_](张一茗)

[SLAM for Dummies][]（一本关于实时定位及绘图（SLAM）的入门指导教程） 提取码：k3r3

[STATE ESTIMATION FOR ROBOTICS][] (吐血推荐) 提取码：y7tc

## 基础 ##

数学基础

*  [计算机视觉中的数学方法][Link 10] 提取码：afyg ----本书着重介绍射影几何学及其在视觉中的应用
 *  [视觉SLAM中的数学基础 第一篇][SLAM_ 1]\----3D空间的位置表示
 *  [视觉SLAM中的数学基础 第二篇][SLAM_ 2]\----四元数
 *  [视觉SLAM中的数学基础 第三篇][SLAM_ 3]\----李群与李代数
 *  [李群和李代数][Link 11] 提取码：92x2

语言编程基础

*  [菜鸟教程][Link 12]\----学习C++与python基础语法
 *  [python计算机视觉编程][python] 提取码：kyt9
 *  [OpenCV3编程入门\_毛星云编著][OpenCV3]\----C++实现 提取码：qnms

计算机视觉基础

*  [计算机视觉算法与应用中文版][Link 13] 提取码：b8y1
 *  [特征提取与图像处理][Link 14] 提取码：hgy2
 *  [机器视觉算法与应用][Link 15] 提取码：hxgn

泡泡机器人SLAM 优质视频课程----视觉slam十四讲

*  [视觉slam十四讲1-2 引言与概述][slam_1-2]
 *  [视觉SLAM十四讲（第三章）][SLAM 4]
 *  [视觉slam第4章][slam_4]
 *  [视觉SLAM十四讲-第五章-相机与图像][SLAM_-_-]
 *  [视觉SLAM十四讲-第六章-非线性优化][SLAM_-_- 1]
 *  [视觉SLAM十四讲-第七章-视觉里程计一][SLAM_-_- 2]

Python + SLAM

*  [用python学习slam系列（一）从图像到点云][python_slam]
 *  [用python学习slam系列（二）特征提取与配准][python_slam 1]

## 进阶 ##

一步步实现SLAM系列教程

*  [一步步实现slam1-项目框架搭建][slam1-]
 *  [一步步实现slam2-orb特征检测][slam2-orb]
 *  [一步步实现slam3-初始位置估计1][slam3-_1]
 *  [一步步实现slam3-初始位置估计2][slam3-_2]

[SLAM最终话：视觉里程计][SLAM 5](高翔博士)

[双目视觉里程计][Link 16](谢晓佳-视频)

[视觉SLAM中的矩阵李群基础][SLAM 6](王京-视频)

[路径规划][Link 17](王超群-视频)

[优化与求解][Link 18](刘毅-视频)

[直接法的原理与实现][Link 19](高翔-视频)

[Course on SLAM][] 提取码：i94s

[LM算法计算单应矩阵][LM]

[激光SLAM][SLAM 7](王龙军)

[我们如何定位SLAM？——关于技术创新、产品开发和管理的经验和教训][SLAM 8]

[语义SLAM的未来与思考(1)][SLAM_1]

[语义SLAM的未来与思考(2)][SLAM_2]

## 优秀文章 ##

泡泡机器人SLAM优秀技术文章

*  [SLAM: 现在，未来和鲁棒年代（一）][SLAM_ 4]
 *  [SLAM: 现在，未来和鲁棒年代（二）][SLAM_ 5]
 *  [SLAM: 现在，未来和鲁棒年代（三）][SLAM_ 6]
 *  [SLAM: 现在，未来和鲁棒年代（四）][SLAM_ 7]
 *  [SLAM: 现在，未来和鲁棒年代（五）][SLAM_ 8]

[SLAM刚刚开始的未来][SLAM 9](张哲)

[2D Slam与3D SLam 的区别到底在哪里][2D Slam_3D SLam]

[研究SLAM，对编程的要求有多高？][SLAM 10]

[SLAM在VR/AR领域重要吗？][SLAM_VR_AR]

[单目SLAM在移动端应用的实现难点有哪些？][SLAM 11]

[机器人的双眸：视觉SLAM是如何实现的？][SLAM 12]

[牛逼哄哄的SLAM技术 即将颠覆哪些领域？][SLAM_ 9]

## 技术博客 ##

[半闲居士][Link 20]\----高翔博士的SLAM博客（力推）

*  [SLAM拾萃(1)：octomap][SLAM_1_octomap]
 *  [视觉SLAM漫谈（二）:图优化理论与g2o的使用][SLAM_g2o]

[白巧克力亦唯心][Link 21]

*  [graph slam tutorial : 从推导到应用1][graph slam tutorial _ _1]
 *  [graph slam tutorial ：从推导到应用２][graph slam tutorial]

[冯兵][Link 22]

*  [视觉里程计简介][Link 23]
 *  [视觉里程计总介绍][Link 24]

[hitcm][]

*  [ROS实时采集Android的图像和IMU数据][ROS_Android_IMU]
 *  [基于点线特征的Kinect2实时环境重建（Tracking and Mapping）][Kinect2_Tracking and Mapping]

[何必浓墨重彩][Link 25]

*  [SLAM代码（优化及常用库）][SLAM 13]
 *  [SLAM代码（多视几何基础)][SLAM 14]
 *  [SLAM代码（三维重建）][SLAM 15]
 *  [SLAM代码（设计模式）][SLAM 16]
 *  [SLAM代码（设计模式2）][SLAM_2 1]

[路游侠][Link 26]

*  [AR中的SLAM][AR_SLAM]
 *  [SVO原理解析][SVO]

[电脑线圈][Link 27]

[wishchin][]

## 网站与研究组织 ##

[泡泡机器人][Link 28]\----泡泡机器人是中国SLAM研究爱好者自发组成的团体，在自愿条件下分享SLAM相关知识，为推动国内SLAM研究做出一点小小的贡献。

[ROSClub机器人俱乐部][ROSClub]\----这是一个完美的ROS机器人开发交流社区平台，在这里你可以找到你所要的！

[SLAMCN][]\-----SLAM精选国内外学习资源

[openslam.org][]\--A good collection of open source code and explanations of SLAM.(推荐)

[易科机器人实验室][Link 29]

[电子发烧友--SLAM][--SLAM]

[电子工程世界--SLAM][--SLAM 1]

Jianxiong Xiao (Professor X)\---从事cv dl与slam相结合的多项研究.

[Robot Mapping][]

[Chuck Palumbo][]\----需要FQ

[Alexander Grau's blog][Alexander Grau_s blog]\----博客里有很多关于机器人, SLAM, 传感器等技术

[Andrew Davison: Research][Andrew Davison_ Research]

[Autonome and Perceptive Systemen][]\---research page at University of Groningen about visual SLAM.

[SLAM Tutorial@ICRA 2016][SLAM Tutorial_ICRA 2016]

[SLAM Summer School][]\----[https://github.com/kanster/awesome-slam\#courses-lectures-and-workshops][https_github.com_kanster_awesome-slam_courses-lectures-and-workshops]

[autoloc][]

## 书籍与资料 ##

[工业机器人视觉系统组成及介绍][Link 30](fu78)

[深度学习][Link 31]（zyn2）

[svo\_lsd][svo_lsd](uyce)

[MEMS IMU的入门与应用 - 胡佳兴][MEMS IMU_ -](vt6m)

[双目视觉里程计][Link 32](27jk)

[高精度实时视觉定位的关键技术研究][Link 33](yrct)

[ORB-SLAM2源码详解][ORB-SLAM2](su4r)

[ORB-SLAM2源码详解-补充H矩阵分解][ORB-SLAM2_-_H](vjik)

[激光slam][slam 1](9dqd)

[图像特征的非刚性匹配][Link 34](w85h)

英文版（有些需FQ）

*  [Current trends in SLAM][]\---关于DTAM,PTAM,SLAM++等系统的对比
 *  [The scaling problem][]\----针对SLAM计算量过大的问题进行讲解
 *  [slamtute1--The Essential Algorithms][]
 *  [A random-finite-set approach to Bayesian SLAM][]
 *  [On the Representation and Estimation of Spatial Uncertainty][]
 *  [Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age][Past_ Present_ and Future of Simultaneous Localization And Mapping_ Towards the Robust-Perception Age](2016)
 *  [Direct Sparse Odometry][]
 *  [Modelling Uncertainty in Deep Learning for Camera Relocalization][]
 *  [Tree-connectivity: Evaluating the graphical structure of SLAM][Tree-connectivity_ Evaluating the graphical structure of SLAM]
 *  [Multi-Level Mapping: Real-time Dense Monocular SLAM][Multi-Level Mapping_ Real-time Dense Monocular SLAM]
 *  [State Estimation for Robotic -- A Matrix Lie Group Approach][]
 *  [Probabilistic Robotics][]\----Dieter Fox, Sebastian Thrun, and Wolfram Burgard, 2005
 *  [Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods][Simultaneous Localization and Mapping for Mobile Robots_ Introduction and Methods]
 *  [An Invitation to 3-D Vision -- from Images to Geometric Models][]\----Yi Ma, Stefano Soatto, Jana Kosecka and Shankar S. Sastry, 2005

## SLAM 方案 ##

ORB-SLAM

*  [ORB-SLAM（一）简介][ORB-SLAM]
 *  [ORB-SLAM（二）性能][ORB-SLAM 1]
 *  [ORB-SLAM（三）地图初始化][ORB-SLAM 2]
 *  [ORB-SLAM（四）追踪][ORB-SLAM 3]
 *  [ORB-SLAM（五）优化][ORB-SLAM 4]
 *  [ORB-SLAM（六）回环检测][ORB-SLAM 5]
 *  [ORB\_SLAM 初接触][ORB_SLAM]
 *  [ORB\_SLAM 初接触2][ORB_SLAM _2]
 *  [ORB\_SLAM - 3：和markerless AR的结合][ORB_SLAM - 3_markerless AR]
 *  [ORB\_SLAM - 4：卡片地图预先创建][ORB_SLAM - 4]
 *  [ORB\_SLAM - 5：SLAM多目标添加][ORB_SLAM - 5_SLAM]
 *  [运行ORB-SLAM笔记\_编译篇（一）][ORB-SLAM 6]\----Being\_young
 *  [运行ORB-SLAM笔记\_使用篇（二）][ORB-SLAM 7]\----Being\_young
 *  [ORB-SLAM][ORB-SLAM 8]\----ORB-SLAM 官方网站
 *  [ORB-SLAM：精确多功能单目SLAM系统][ORB-SLAM_SLAM]\----中文翻译
 *  [视觉SLAM实战：ORB-SLAM2 with Kinect2][SLAM_ORB-SLAM2 with Kinect2]
 *  [ORB-SLAM--- 让程序飞起来][ORB-SLAM---]
 *  [ORB-SLAM 笔记][ORB-SLAM 9]

RGB-SLAM

*  [视觉SLAM实战（一）：RGB-D SLAM V2][SLAM_RGB-D SLAM V2]
 *  [一起做RGB-D SLAM (2)][RGB-D SLAM _2]
 *  [一起做RGB-D SLAM (3)][RGB-D SLAM _3]
 *  [一起做RGB-D SLAM (4)][RGB-D SLAM _4]
 *  [一起做RGB-D SLAM (5)][RGB-D SLAM _5]
 *  [一起做RGB-D SLAM (6)][RGB-D SLAM _6]
 *  [一起做RGB-D SLAM(7) （完结篇）][RGB-D SLAM_7_]
 *  [一起做RGB-D SLAM(8) （关于调试与补充内容）][RGB-D SLAM_8_]
 *  [一起做RGB-D SLAM (9)--问题总结][RGB-D SLAM _9_--]

PTAM单目

*  [PTAM算法流程介绍][PTAM]
 *  [Parallel Tracking and Mapping for Small AR Workspaces][]
 *  [PTAM跟踪过程中的旋转预测方法][PTAM 1]
 *  [PTAM跟踪失败后的重定位][PTAM 2]

LSD-SLAM

*  [LSD-SLAM深入学习（1）-基本介绍与ros下的安装][LSD-SLAM_1_-_ros]
 *  [LSD-SLAM深入学习（2）-算法解析][LSD-SLAM_2_-]
 *  [LSD-SLAM深入学习（3）-代码解析][LSD-SLAM_3_-]
 *  [LSD-SLAM: Large-Scale Direct Monocular SLAM][LSD-SLAM_ Large-Scale Direct Monocular SLAM]\----Computer Vision Group
 *  [lsd-slam源码解读第一篇:Sophus/sophus][lsd-slam_Sophus_sophus]
 *  [lsd-slam源码解读第二篇:DataStructures][lsd-slam_DataStructures]
 *  [lsd-slam源码解读第三篇:算法解析][lsd-slam]
 *  [lsd-slam源码解读第四篇:tracking][lsd-slam_tracking]
 *  [lsd-slam源码解读第五篇:DepthEstimation][lsd-slam_DepthEstimation]
 *  [sd-slam源码解读第六篇:GlobalMapping][sd-slam_GlobalMapping]

DSO单目

*  [DSO: Direct Sparse Odometry][DSO_ Direct Sparse Odometry]
 *  [DSO论文速递（一）----泡泡机器人][DSO_----]
 *  [DSO论文速递（二）----泡泡机器人][DSO_---- 1]
 *  [DSO论文速递（三）----泡泡机器人][DSO_---- 2]
 *  [DSO 初探][DSO]\----白巧克力亦唯心
 *  [基于视觉+惯性传感器的空间定位方法][Link 35]

SVO单目

*  [svo： semi-direct visual odometry 论文解析][svo_ semi-direct visual odometry]
 *  [安装说明][Link 36]
 *  [安装SVO][SVO 1]
 *  [SLAM代码之svo代码分析][SLAM_svo]

DTAM

*  [OpenDTAM][]\----An open source implementation of DTAM

## 优秀案例 ##

[ORB\_SLAM][ORB_SLAM 1]\----多功能和单目的SLAM框架

[ORB\_SLAM2][ORB_SLAM2]\----Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

[LSD-SLAM][]\----很有名的，不多解释了

[DVO-SLAM][]\----Dense Visual Odometry and SLAM

[RGBD-SLAM2][]\----RGB-D SLAM for ROS

[SVO][SVO 2]\----Semi-Direct Monocular Visual Odometry

[G2O][]\----A General Framework for Graph Optimization

[cartographer][]\----这是一个提供实时SLAM在2D和3D的跨多个平台和传感器配置。

[slambook][]\----高翔博士的SLAM书籍中的code

[slamhound][]\----Slamhound rips your namespace form apart and reconstructs it.

[ElasticFusion][]\----Real-time dense visual SLAM system

[ORB\_SLAM\_iOS][ORB_SLAM_iOS]\----ORB\_SLAM for iOS

[ORB\_SLAM2\_Android][ORB_SLAM2_Android]\----a repository for ORB\_SLAM2 in Android

## 泡泡机器人公开课 ##

[【泡泡机器人公开课】第二课：深度学习及应用][Link 37]

[【泡泡机器人公开课】第三课 SVO 和 LSD\_SLAM解析][SVO _ LSD_SLAM]

[【泡泡机器人公开课】第四课：Caffe入门与应用 by 高翔][Caffe_ by]

[【泡泡机器人公开课】第五课：双目视觉里程计][Link 38]

[【泡泡机器人公开课】第六课：比特币介绍 by 李其乐][by]

[【泡泡机器人公开课】第七课：增强现实及其应用][Link 39]

[【泡泡机器人公开课】第八课：MEMS IMU的入门与应用][MEMS IMU]

[【泡泡机器人公开课】第九课 双目校正及视差图的计算][Link 40]

[【泡泡机器人公开课】第十课 IMU+动态背景消除][IMU]

[【泡泡机器人公开课】第十一课：COP-SLAM by 杨俊][COP-SLAM by]

[【泡泡机器人公开课】第十二课：SLAM综述ORB-LSD-SVO by 刘浩敏][SLAM_ORB-LSD-SVO by]

[【泡泡机器人公开课】第十三课：CUDA 优化代码 by 张也冬][CUDA _ by]

[【泡泡机器人公开课】第十四课：KinectFusion、ElasticFusion 论文和代码解析][KinectFusion_ElasticFusion]

[【泡泡机器人公开课】第十五课：视觉SLAM中的矩阵李群基础][SLAM 17]

[【泡泡机器人公开课】第十六课：rosbridge原理及应用][rosbridge]

[【泡泡机器人公开课】第十七课：SLAM 优化与求解][SLAM 18]

[【泡泡机器人公开课】第十八课：Direct方法的原理与实现][Direct]

[【泡泡机器人公开课】第十九课：图像技术在AR中的实践][AR]

[【泡泡机器人公开课】第二十课：路径规划][Link 41]

[【泡泡机器人公开课】第二十一课：ORB-SLAM简单重构][ORB-SLAM 10]

[【泡泡机器人公开课】第二十二课：LeastSquare\_and\_gps\_fusion][LeastSquare_and_gps_fusion]

[【泡泡机器人公开课】第二十三课：Scan Matching in 2D SLAM][Scan Matching in 2D SLAM]

[【泡泡机器人公开课】第二十四课：LSD-SLAM深度解析][LSD-SLAM 1]

[【泡泡机器人公开课】第二十五课：激光SLAM][SLAM 19]

[【泡泡机器人公开课】第二十六课：TSL安全网络传输协议简介][TSL]

[【泡泡机器人公开课】第二十七课：Textureless Object Tracking][Textureless Object Tracking]

[【泡泡机器人公开课】第二十八课：基于光流的视觉控制][Link 42]

[【泡泡机器人公开课】第二十九课：Robust Camera Location Estimation][Robust Camera Location Estimation]

[【泡泡机器人公开课】第三十课:非线性优化与g2o][g2o]

[【泡泡机器人公开课】第三十一课：G2O简介][G2O 1]

[【泡泡机器人公开课】第三十二课：我们如何定位SLAM？][SLAM 20]

[【泡泡机器人公开课】第三十三课：矩阵流形上的优化介绍][Link 43]

[【泡泡机器人公开课】第三十四课：里程计-视觉融合SLAM][-_SLAM]

[【泡泡机器人公开课】第三十五课：Visualization in SLAM][Visualization in SLAM]

[【泡泡机器人公开课】第三十六课：ORB-SLAM2源码详解][ORB-SLAM2 1]

[【泡泡机器人公开课】第三十七课：Absolute Scale Estimation and Correction][Absolute Scale Estimation and Correction]

[【泡泡机器人公开课】第三十八课：Structure Light Based�3D Surface Imaging][Structure Light Based_3D Surface Imaging]

[【泡泡机器人公开课】第三十九课：PnP)算法简介与代码解析][PnP]

[转自dzyBK][dzyBK]

[Link 1]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E5%85%A5%E9%97%A8
[Link 2]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E5%9F%BA%E7%A1%80
[Link 3]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E8%BF%9B%E9%98%B6
[Link 4]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E4%BC%98%E7%A7%80%E6%96%87%E7%AB%A0
[Link 5]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E6%8A%80%E6%9C%AF%E5%8D%9A%E5%AE%A2
[Link 6]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E7%BD%91%E7%AB%99%E4%B8%8E%E7%A0%94%E7%A9%B6%E7%BB%84%E7%BB%87
[Link 7]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E4%B9%A6%E7%B1%8D%E4%B8%8E%E8%B5%84%E6%96%99
[SLAM]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#SLAM%E6%96%B9%E6%A1%88
[Link 8]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E4%BC%98%E7%A7%80%E6%A1%88%E4%BE%8B
[Link 9]: https://github.com/GeekLiB/Lee-SLAM-source?utm_source=tuicool&utm_medium=referral#%E6%B3%A1%E6%B3%A1%E6%9C%BA%E5%99%A8%E4%BA%BA%E4%B8%93%E6%A0%8F%E5%85%AC%E5%BC%80%E8%AF%BE
[SLAM_-]: http://www.bilibili.com/video/av5911960/?from=search&seid=375069506917728550
[slam]: http://blog.csdn.net/yimingsilence/article/details/51701944
[SLAM 1]: https://zhuanlan.zhihu.com/p/21381490
[SLAM 2]: http://www.leiphone.com/news/201609/iAe3f8qmRHXavgSl.html?viewType=weixin
[SLAM 3]: https://wenku.baidu.com/view/905bf05d312b3169a451a495.html
[SLAM_]: http://www.leiphone.com/news/201605/5etiwlnkWnx7x0zb.html
[SLAM for Dummies]: https://pan.baidu.com/s/1dFxKLZb
[STATE ESTIMATION FOR ROBOTICS]: https://pan.baidu.com/s/1pLO4Nwv
[Link 10]: https://pan.baidu.com/s/1pLwK4uJ
[SLAM_ 1]: http://www.cnblogs.com/gaoxiang12/p/5113334.html
[SLAM_ 2]: http://www.cnblogs.com/gaoxiang12/p/5120175.html
[SLAM_ 3]: http://www.cnblogs.com/gaoxiang12/p/5137454.html
[Link 11]: https://pan.baidu.com/s/1eRUC3ke
[Link 12]: http://www.runoob.com/
[python]: https://pan.baidu.com/s/1bpcQlvp
[OpenCV3]: https://pan.baidu.com/s/1i4Gtv3B
[Link 13]: https://pan.baidu.com/s/1dFHxDiL
[Link 14]: https://pan.baidu.com/s/1nvseOf3
[Link 15]: https://pan.baidu.com/s/1i4O0LOp
[slam_1-2]: http://www.bilibili.com/video/av7494417/?from=search&seid=375069506917728550
[SLAM 4]: http://www.bilibili.com/video/av7612959/?from=search&seid=375069506917728550
[slam_4]: http://www.bilibili.com/video/av7705856/?from=search&seid=375069506917728550
[SLAM_-_-]: http://www.bilibili.com/video/av7816357/?from=search&seid=375069506917728550
[SLAM_-_- 1]: http://www.bilibili.com/video/av7921657/?from=search&seid=375069506917728550
[SLAM_-_- 2]: http://www.bilibili.com/video/av8061127/?from=search&seid=375069506917728550
[python_slam]: http://www.rosclub.cn/post-682.html
[python_slam 1]: http://www.rosclub.cn/post-684.html
[slam1-]: http://fengbing.net/2016/02/03/%E4%B8%80%E6%AD%A5%E6%AD%A5%E5%AE%9E%E7%8E%B0slam1-%E6%A1%86%E6%9E%B6%E6%90%AD%E5%BB%BA/
[slam2-orb]: http://fengbing.net/2016/04/03/%E4%B8%80%E6%AD%A5%E6%AD%A5%E5%AE%9E%E7%8E%B0slam2-orb%E7%89%B9%E5%BE%81%E6%A3%80%E6%B5%8B/
[slam3-_1]: http://fengbing.net/2016/04/23/%E4%B8%80%E6%AD%A5%E6%AD%A5%E5%AE%9E%E7%8E%B0slam3-%E5%88%9D%E5%A7%8B%E4%BD%8D%E5%A7%BF%E4%BC%B0%E8%AE%A11/
[slam3-_2]: http://fengbing.net/2016/04/24/%E4%B8%80%E6%AD%A5%E6%AD%A5%E5%AE%9E%E7%8E%B0slam3-%E5%88%9D%E5%A7%8B%E4%BD%8D%E5%A7%BF%E4%BC%B0%E8%AE%A12/
[SLAM 5]: http://www.leiphone.com/news/201609/Qj6uJhaywpBD8vdq.html
[Link 16]: http://www.bilibili.com/video/av5913124/
[SLAM 6]: http://www.bilibili.com/video/av6069884/
[Link 17]: http://www.bilibili.com/video/av6640192/
[Link 18]: http://www.bilibili.com/video/av6298224/
[Link 19]: http://www.bilibili.com/video/av6299156/
[Course on SLAM]: https://pan.baidu.com/s/1miuOIUW
[LM]: https://mp.weixin.qq.com/s?__biz=MzI5MTM1MTQwMw==&mid=2247484602&idx=1&sn=b6d4b9d24af02a1e8de7f30e7f17f525&chksm=ec10babedb6733a8c5b4ff4877b250394797efff616647778885515991daf25e27f2cd0f9914&mpshare=1&scene=24&srcid=0323y0KxEHYSArWp9ldTTSOi&key=0722bcaff7a71b24fa77c83e37758d99034902520ffb87ae1ceeaed5271181bc7a04c3cab7ed2588574061afc774ff7c19c8538b91f113a45b4f7edb666ccdff2b6a60c60746cff9ef32d749f0f7e87f&ascene=0&uin=NTA0OTM2NzY%3D&devicetype=iMac+MacBookAir7%2C2+OSX+OSX+10.12+build%2816A323%29&version=12020010&nettype=WIFI&fontScale=100&pass_ticket=XHDonKi50slr29BQ9oY9LM0lAhnHy33o2h%2Fz2ho0874%3D
[SLAM 7]: https://mp.weixin.qq.com/s?__biz=MzI5MTM1MTQwMw==&mid=2247484587&idx=1&sn=82c66613817bd6f50f58cd309dc48a6a&chksm=ec10baafdb6733b9ce69ef19f27087ab8ebfc40d479fc5f0469c301d414c3745d6abb02e2d8b&mpshare=1&scene=24&srcid=0323ANeCiITgcqDmjeIQZ7Li&key=a4c24fb23da90f2ca36bf82f0a48f6a72ddb40abe90030450b2d73544285ef7c297334f0b202b66bddc6aee8ff556fa9c0ac3d4178332056bea0f16171e090921d01980d4007b6102671f14f8b1af8e9&ascene=0&uin=NTA0OTM2NzY%3D&devicetype=iMac+MacBookAir7%2C2+OSX+OSX+10.12+build%2816A323%29&version=12020010&nettype=WIFI&fontScale=100&pass_ticket=XHDonKi50slr29BQ9oY9LM0lAhnHy33o2h%2Fz2ho0874%3D
[SLAM 8]: https://mp.weixin.qq.com/s?__biz=MzI5MTM1MTQwMw==&mid=2247484979&idx=1&sn=3d4af432a50842360f31561dbabfa58b&chksm=ec10b837db673121941d8c3e1c8492238f6922b3223b397b399f0066be03171a9146d6c0c939&mpshare=1&scene=24&srcid=0323oLiJv6WiRX2odtfQDXPe&key=a4c24fb23da90f2ca935bf18db801448a4369496fff7ca8e359883d8b14cc7b482b81a7bc8d50d9165bb8e2a99056a1b79bc3e423cfdd735279a28883133cf50a7ae158b88b39b1a33477e71788b8e5b&ascene=0&uin=NTA0OTM2NzY%3D&devicetype=iMac+MacBookAir7%2C2+OSX+OSX+10.12+build%2816A323%29&version=12020010&nettype=WIFI&fontScale=100&pass_ticket=XHDonKi50slr29BQ9oY9LM0lAhnHy33o2h%2Fz2ho0874%3D
[SLAM_1]: https://mp.weixin.qq.com/s?__biz=MzI5MTM1MTQwMw==&mid=2247485956&idx=1&sn=3d95d417c7a1446a90276473ec736f0b&chksm=ec10b400db673d168f0c34245c58f9c6fbf339be3366689537468fa5ea84e92a964c92dc8be3&mpshare=1&scene=24&srcid=0323LglzpLJ5ftLN1isUQEc7&key=04a263dc798cf3e2798bd64119c159030a49ead5db2e70090701706793c09e38d26018f0415fe1d986020f20cd29987e51c790ceee046946112b55ded02fc28ccdc2392550a895bf8c1a8515cdc87fb9&ascene=0&uin=NTA0OTM2NzY%3D&devicetype=iMac+MacBookAir7%2C2+OSX+OSX+10.12+build%2816A323%29&version=12020010&nettype=WIFI&fontScale=100&pass_ticket=XHDonKi50slr29BQ9oY9LM0lAhnHy33o2h%2Fz2ho0874%3D
[SLAM_2]: https://mp.weixin.qq.com/s?__biz=MzI5MTM1MTQwMw==&mid=2247486496&idx=1&sn=672421edb67a7566a8d3629596f12496&chksm=ec10b224db673b3245d7c49ac07b9e7e924b07d93992c0a4392649624178a614eb084eee5cd7&mpshare=1&scene=24&srcid=0323rFVB2RhlBb8YrM7zYgyo&key=405f89b14d07d74b9f658163a8b0fb12e76b79928dfd59dd093a011fc98c93a37d0b489893c3d90a6e2e5b8516f05b0443ac35204d4c2e3c1f28398ff9d48148aa69f818c141f08503c15445b4af2375&ascene=0&uin=NTA0OTM2NzY%3D&devicetype=iMac+MacBookAir7%2C2+OSX+OSX+10.12+build%2816A323%29&version=12020010&nettype=WIFI&fontScale=100&pass_ticket=XHDonKi50slr29BQ9oY9LM0lAhnHy33o2h%2Fz2ho0874%3D
[SLAM_ 4]: http://weixin.niurenqushi.com/article/2017-02-12/4766381.html
[SLAM_ 5]: http://weixin.niurenqushi.com/article/2017-02-13/4767586.html
[SLAM_ 6]: http://weixin.niurenqushi.com/article/2017-02-14/4768761.html
[SLAM_ 7]: https://mp.weixin.qq.com/s?__biz=MzI5MTM1MTQwMw==&mid=2247488263&idx=1&sn=1c10dbf32bfd90c3587988652df6187d&chksm=ec10ad03db672415dcea09f62f2341fd330895c71c77b04a92d6be3e3f0274eb2771a07354dd&mpshare=1&scene=24&srcid=0323gxrX4cn4zd4zY4dZcIcd&key=3c2da574259c4c3bab55c1c5c0eab459ad4b990e6130aed37d181792a2918d8c8ab73d84eb0872e0631e5c953289d05de5e32588c28a8c899225e45087d67cb4577a806dfce9d5b23eb5f099c7cc8af4&ascene=0&uin=NTA0OTM2NzY%3D&devicetype=iMac+MacBookAir7%2C2+OSX+OSX+10.12+build%2816A323%29&version=12020010&nettype=WIFI&fontScale=100&pass_ticket=BNJCJrAc4xlKLazxgWI8g7b%2BvcGziaU7%2Bs7XLYj8ASQ%3D
[SLAM_ 8]: http://weixin.niurenqushi.com/article/2017-02-25/4779559.html
[SLAM 9]: http://weibo.com/ttarticle/p/show?id=2309403994589869514382&mod=zwenzhang
[2D Slam_3D SLam]: http://www.arjiang.com/index.php?m=content&c=index&a=show&catid=11&id=418
[SLAM 10]: https://www.zhihu.com/question/51707998
[SLAM_VR_AR]: https://www.zhihu.com/question/37071486
[SLAM 11]: https://www.zhihu.com/question/50385799
[SLAM 12]: http://www.leiphone.com/news/201607/GLQj0wrjKD4eHvq5.html
[SLAM_ 9]: http://www.leiphone.com/news/201605/oj1lxZVPulRdNxYt.html
[Link 20]: http://www.cnblogs.com/gaoxiang12
[SLAM_1_octomap]: http://www.cnblogs.com/gaoxiang12/p/5041142.html
[SLAM_g2o]: http://www.cnblogs.com/gaoxiang12/p/3776107.html
[Link 21]: http://blog.csdn.net/heyijia0327
[graph slam tutorial _ _1]: http://blog.csdn.net/heyijia0327/article/details/47686523
[graph slam tutorial]: http://blog.csdn.net/heyijia0327/article/details/47731631
[Link 22]: http://fengbing.net/
[Link 23]: http://fengbing.net/2015/07/25/%E8%A7%86%E8%A7%89%E9%87%8C%E7%A8%8B%E8%AE%A1%E7%AE%80%E4%BB%8B/
[Link 24]: http://fengbing.net/2015/08/01/%E8%A7%86%E8%A7%89%E9%87%8C%E7%A8%8B%E8%AE%A1%E6%80%BB%E4%BB%8B%E7%BB%8D/
[hitcm]: http://www.cnblogs.com/hitcm/
[ROS_Android_IMU]: http://www.cnblogs.com/hitcm/p/5616364.html
[Kinect2_Tracking and Mapping]: http://www.cnblogs.com/hitcm/p/5245463.html
[Link 25]: http://blog.csdn.net/wendox/article/category/6555599
[SLAM 13]: http://blog.csdn.net/wendox/article/details/52507220
[SLAM 14]: http://blog.csdn.net/wendox/article/details/52552286
[SLAM 15]: http://blog.csdn.net/wendox/article/details/52719252
[SLAM 16]: http://blog.csdn.net/wendox/article/details/53454768
[SLAM_2 1]: http://blog.csdn.net/wendox/article/details/53489982
[Link 26]: http://www.cnblogs.com/luyb/
[AR_SLAM]: http://www.cnblogs.com/luyb/p/6481725.html
[SVO]: http://www.cnblogs.com/luyb/p/5773691.html
[Link 27]: https://zhuanlan.zhihu.com/computercoil
[wishchin]: http://blog.csdn.net/wishchin/article/category/5723249/2
[Link 28]: http://space.bilibili.com/38737757/#%21/
[ROSClub]: http://www.rosclub.cn/cate-9.html
[SLAMCN]: http://www.slamcn.org/index.php/%E9%A6%96%E9%A1%B5
[openslam.org]: http://openslam.org/
[Link 29]: http://blog.exbot.net/
[--SLAM]: http://www.elecfans.com/tags/slam/
[--SLAM 1]: http://www.eeworld.com.cn/tags/SLAM
[Robot Mapping]: http://ais.informatik.uni-freiburg.de/teaching/ws13/mapping/
[Chuck Palumbo]: http://www.discovery.com/tv-shows/rusted-development/hosts/chuck-palumbo/
[Alexander Grau_s blog]: http://grauonline.de/wordpress/
[Andrew Davison_ Research]: https://www.doc.ic.ac.uk/~ajd/index.html
[Autonome and Perceptive Systemen]: http://www.ai.rug.nl/~gert/as/
[SLAM Tutorial_ICRA 2016]: http://www.dis.uniroma1.it/~labrococo/tutorial_icra_2016/
[SLAM Summer School]: http://www.acfr.usyd.edu.au/education/summerschool.shtml
[https_github.com_kanster_awesome-slam_courses-lectures-and-workshops]: https://github.com/kanster/awesome-slam#courses-lectures-and-workshops
[autoloc]: http://webdiis.unizar.es/~neira/slam.html
[Link 30]: https://pan.baidu.com/s/1gf1KEdX
[Link 31]: https://pan.baidu.com/s/1jIKBwSu
[svo_lsd]: https://pan.baidu.com/s/1kV5apsN
[MEMS IMU_ -]: https://pan.baidu.com/s/1o8M5fSY
[Link 32]: https://pan.baidu.com/s/1nvv2M6l
[Link 33]: https://pan.baidu.com/s/1dEJj1Ln
[ORB-SLAM2]: https://pan.baidu.com/s/1ceoq78
[ORB-SLAM2_-_H]: https://pan.baidu.com/s/1mhVg2ta
[slam 1]: https://pan.baidu.com/s/1i5QJeYx
[Link 34]: https://pan.baidu.com/s/1eRNRf1o
[Current trends in SLAM]: http://webdiis.unizar.es/~neira/SLAM/SLAM_5_Trends.pdf
[The scaling problem]: http://webdiis.unizar.es/~neira/SLAM/SLAM_4_Scaling.pptx.pdf
[slamtute1--The Essential Algorithms]: http://www-personal.acfr.usyd.edu.au/tbailey/papers/slamtute1.pdf
[A random-finite-set approach to Bayesian SLAM]: http://staffhome.ecm.uwa.edu.au/~00053612/vo/MVAV_SLAM11.pdf
[On the Representation and Estimation of Spatial Uncertainty]: http://www.frc.ri.cmu.edu/~hpm/project.archive/reference.file/Smith&Cheeseman.pdf
[Past_ Present_ and Future of Simultaneous Localization And Mapping_ Towards the Robust-Perception Age]: https://arxiv.org/abs/1606.05830
[Direct Sparse Odometry]: https://arxiv.org/abs/1607.02565
[Modelling Uncertainty in Deep Learning for Camera Relocalization]: https://arxiv.org/abs/1509.05909
[Tree-connectivity_ Evaluating the graphical structure of SLAM]: http://ieeexplore.ieee.org/document/7487264/
[Multi-Level Mapping_ Real-time Dense Monocular SLAM]: https://groups.csail.mit.edu/rrg/papers/greene_icra16.pdf
[State Estimation for Robotic -- A Matrix Lie Group Approach]: http://asrl.utias.utoronto.ca/~tdb/bib/barfoot_ser15.pdf
[Probabilistic Robotics]: http://www.probabilistic-robotics.org/
[Simultaneous Localization and Mapping for Mobile Robots_ Introduction and Methods]: http://www.igi-global.com/book/simultaneous-localization-mapping-mobile-robots/66380
[An Invitation to 3-D Vision -- from Images to Geometric Models]: http://vision.ucla.edu/MASKS/
[ORB-SLAM]: http://www.cnblogs.com/luyb/p/5215168.html
[ORB-SLAM 1]: http://www.cnblogs.com/luyb/p/5240168.html
[ORB-SLAM 2]: http://www.cnblogs.com/luyb/p/5260785.html
[ORB-SLAM 3]: http://www.cnblogs.com/luyb/p/5357790.html
[ORB-SLAM 4]: http://www.cnblogs.com/luyb/p/5447497.html
[ORB-SLAM 5]: http://www.cnblogs.com/luyb/p/5599042.html
[ORB_SLAM]: https://zhuanlan.zhihu.com/p/20589372
[ORB_SLAM _2]: https://zhuanlan.zhihu.com/p/20596486
[ORB_SLAM - 3_markerless AR]: https://zhuanlan.zhihu.com/p/20599601
[ORB_SLAM - 4]: https://zhuanlan.zhihu.com/p/20602540
[ORB_SLAM - 5_SLAM]: https://zhuanlan.zhihu.com/p/20608728
[ORB-SLAM 6]: http://www.cnblogs.com/li-yao7758258/p/5906447.html
[ORB-SLAM 7]: http://www.cnblogs.com/li-yao7758258/p/5912663.html
[ORB-SLAM 8]: http://webdiis.unizar.es/~raulmur/orbslam/
[ORB-SLAM_SLAM]: http://qiqitek.com/blog/?p=13
[SLAM_ORB-SLAM2 with Kinect2]: http://www.cnblogs.com/gaoxiang12/p/5161223.html
[ORB-SLAM---]: http://blog.csdn.net/dourenyin/article/details/48055441
[ORB-SLAM 9]: http://blog.csdn.net/fuxingyin/article/details/53511439
[SLAM_RGB-D SLAM V2]: http://www.cnblogs.com/gaoxiang12/p/4462518.html
[RGB-D SLAM _2]: http://www.cnblogs.com/gaoxiang12/p/4652478.html
[RGB-D SLAM _3]: http://www.cnblogs.com/gaoxiang12/p/4659805.html
[RGB-D SLAM _4]: http://www.cnblogs.com/gaoxiang12/p/4669490.html
[RGB-D SLAM _5]: http://www.cnblogs.com/gaoxiang12/p/4719156.html
[RGB-D SLAM _6]: http://www.cnblogs.com/gaoxiang12/p/4739934.html
[RGB-D SLAM_7_]: http://www.cnblogs.com/gaoxiang12/p/4754948.html
[RGB-D SLAM_8_]: http://www.cnblogs.com/gaoxiang12/p/4770813.html
[RGB-D SLAM _9_--]: http://www.rosclub.cn/post-85.html
[PTAM]: http://blog.csdn.net/zzzblog/article/details/14455463
[Parallel Tracking and Mapping for Small AR Workspaces]: http://www.robots.ox.ac.uk/~gk/PTAM/
[PTAM 1]: https://zhuanlan.zhihu.com/p/20302059?refer=computercoil
[PTAM 2]: https://zhuanlan.zhihu.com/p/20308700
[LSD-SLAM_1_-_ros]: http://www.cnblogs.com/hitcm/p/4907465.html
[LSD-SLAM_2_-]: http://www.cnblogs.com/hitcm/p/4907536.html
[LSD-SLAM_3_-]: http://www.cnblogs.com/hitcm/p/4887345.html
[LSD-SLAM_ Large-Scale Direct Monocular SLAM]: http://vision.in.tum.de/research/vslam/lsdslam
[lsd-slam_Sophus_sophus]: http://blog.csdn.net/lancelot_vim/article/details/51706832
[lsd-slam_DataStructures]: http://blog.csdn.net/lancelot_vim/article/details/51708412
[lsd-slam]: http://blog.csdn.net/lancelot_vim/article/details/51730676
[lsd-slam_tracking]: http://blog.csdn.net/lancelot_vim/article/details/51758870
[lsd-slam_DepthEstimation]: http://blog.csdn.net/lancelot_vim/article/details/51789318
[sd-slam_GlobalMapping]: http://blog.csdn.net/lancelot_vim/article/details/51812484
[DSO_ Direct Sparse Odometry]: http://vision.in.tum.de/research/vslam/dso
[DSO_----]: http://www.zglwfww.com/a/dajiadouzaikan/2016/1216/5775.html
[DSO_---- 1]: http://diyitui.com/content-1482249289.66463991.html
[DSO_---- 2]: http://diyitui.com/content-1482851742.66460941.html
[DSO]: http://blog.csdn.net/heyijia0327/article/details/53173146
[Link 35]: https://zhuanlan.zhihu.com/p/24072804
[svo_ semi-direct visual odometry]: http://blog.csdn.net/heyijia0327/article/details/51083398
[Link 36]: https://github.com/uzh-rpg/rpg_svo/wiki
[SVO 1]: http://blog.sina.com.cn/s/blog_7b83134b0102wfu4.html
[SLAM_svo]: http://blog.csdn.net/wendox/article/details/52536706
[OpenDTAM]: https://github.com/anuranbaka/OpenDTAM
[ORB_SLAM 1]: https://github.com/raulmur/ORB_SLAM
[ORB_SLAM2]: https://github.com/raulmur/ORB_SLAM2
[LSD-SLAM]: https://github.com/tum-vision/lsd_slam
[DVO-SLAM]: https://github.com/tum-vision/dvo_slam
[RGBD-SLAM2]: https://github.com/felixendres/rgbdslam_v2
[SVO 2]: https://github.com/uzh-rpg/rpg_svo
[G2O]: https://github.com/RainerKuemmerle/g2o
[cartographer]: https://github.com/googlecartographer/cartographer
[slambook]: https://github.com/gaoxiang12/slambook
[slamhound]: https://github.com/technomancy/slamhound
[ElasticFusion]: https://github.com/mp3guy/ElasticFusion
[ORB_SLAM_iOS]: https://github.com/egoist-sx/ORB_SLAM_iOS
[ORB_SLAM2_Android]: https://github.com/FangGet/ORB_SLAM2_Android
[Link 37]: http://www.rosclub.cn/post-212.html
[SVO _ LSD_SLAM]: http://www.rosclub.cn/post-213.html
[Caffe_ by]: http://www.rosclub.cn/post-216.html
[Link 38]: http://www.rosclub.cn/post-217.html
[by]: http://www.rosclub.cn/post-218.html
[Link 39]: http://www.rosclub.cn/post-220.html
[MEMS IMU]: http://www.rosclub.cn/post-221.html
[Link 40]: http://www.rosclub.cn/post-222.html
[IMU]: http://www.rosclub.cn/post-223.html
[COP-SLAM by]: http://www.rosclub.cn/post-224.html
[SLAM_ORB-LSD-SVO by]: http://www.rosclub.cn/post-225.html
[CUDA _ by]: http://www.rosclub.cn/post-226.html
[KinectFusion_ElasticFusion]: http://www.rosclub.cn/post-227.html
[SLAM 17]: http://www.rosclub.cn/post-228.html
[rosbridge]: http://www.rosclub.cn/post-229.html
[SLAM 18]: http://www.rosclub.cn/post-230.html
[Direct]: http://www.rosclub.cn/post-231.html
[AR]: http://www.rosclub.cn/post-232.html
[Link 41]: http://www.rosclub.cn/post-233.html
[ORB-SLAM 10]: http://www.rosclub.cn/post-234.html
[LeastSquare_and_gps_fusion]: http://www.rosclub.cn/post-235.html
[Scan Matching in 2D SLAM]: http://www.rosclub.cn/post-236.html
[LSD-SLAM 1]: http://www.rosclub.cn/post-237.html
[SLAM 19]: http://www.rosclub.cn/post-238.html
[TSL]: http://www.rosclub.cn/post-240.html
[Textureless Object Tracking]: http://www.rosclub.cn/post-242.html
[Link 42]: http://www.rosclub.cn/post-243.html
[Robust Camera Location Estimation]: http://www.rosclub.cn/post-244.html
[g2o]: http://www.rosclub.cn/post-245.html
[G2O 1]: http://www.rosclub.cn/post-247.html
[SLAM 20]: http://www.rosclub.cn/post-499.html
[Link 43]: http://www.rosclub.cn/post-500.html
[-_SLAM]: http://www.rosclub.cn/post-502.html
[Visualization in SLAM]: http://www.rosclub.cn/post-504.html
[ORB-SLAM2 1]: http://www.rosclub.cn/post-505.html
[Absolute Scale Estimation and Correction]: http://www.rosclub.cn/post-517.html
[Structure Light Based_3D Surface Imaging]: http://www.rosclub.cn/post-564.html
[PnP]: http://www.rosclub.cn/post-566.html
[dzyBK]: http://www.cnblogs.com/dzyBK/p/6622390.html