97项开源视觉SLAM方案（一）

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一点人工一点智能 2022-12-29 11:18:45 博主文章分类：SLAM

文章标签 自动驾驶计算机视觉 slam github sed 文章分类 虚拟化云计算

本文简单将各种方案分为以下 7 类（固然有不少文章无法恰当分类，比如动态语义稠密建图的 VISLAM +_+）：

Geometric SLAM
Semantic / Deep SLAM
Multi-Landmarks / Object SLAM
Sensor Fusion
Dynamic SLAM
Mapping
Optimization

本文将列出22个Geometric SLAM开源方案

1. PTAM
· 论文：Klein G, Murray D. Parallel tracking and mapping for small AR workspaces[C]//Mixed and Augmented Reality, 2007. ISMAR 2007. 6th IEEE and ACM International Symposium on. IEEE, 2007: 225-234.
· 代码：https://github.com/Oxford-PTAM/PTAM-GPL
· 工程地址：http://www.robots.ox.ac.uk/~gk/PTAM/
· 作者其他研究：http://www.robots.ox.ac.uk/~gk/publications.html
2. S-PTAM（双目 PTAM）
· 论文：Taihú Pire,Thomas Fischer, Gastón Castro, Pablo De Cristóforis, Javier Civera and Julio Jacobo Berlles. S-PTAM: Stereo Parallel Tracking and Mapping. Robotics and Autonomous Systems, 2017.
· 代码：https://github.com/lrse/sptam
· 作者其他论文：Castro G, Nitsche M A, Pire T, et al. Efficient on-board Stereo SLAM through constrained-covisibility strategies[J]. Robotics and Autonomous Systems, 2019.
3. MonoSLAM
· 论文：Davison A J, Reid I D, Molton N D, et al. MonoSLAM: Real-time single camera SLAM[J]. IEEE transactions on pattern analysis and machine intelligence, 2007, 29(6): 1052-1067.
· 代码：https://github.com/hanmekim/SceneLib2
4. ORB-SLAM2
· 论文：Mur-Artal R, Tardós J D. Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras[J]. IEEE Transactions on Robotics, 2017, 33(5): 1255-1262.
· 代码：https://github.com/raulmur/ORB_SLAM2
· 作者其他论文：
o 单目半稠密建图：Mur-Artal R, Tardós J D. Probabilistic Semi-Dense Mapping from Highly Accurate Feature-Based Monocular SLAM[C]//Robotics: Science and Systems. 2015, 2015.
o VIORB：Mur-Artal R, Tardós J D. Visual-inertial monocular SLAM with map reuse[J]. IEEE Robotics and Automation Letters, 2017, 2(2): 796-803.
o 多地图：Elvira R, Tardós J D, Montiel J M M. ORBSLAM-Atlas: a robust and accurate multi-map system[J]. arXiv preprint arXiv:1908.11585, 2019.

以下5, 6, 7, 8几项是 TUM 计算机视觉组全家桶，官方主页：https://vision.in.tum.de/research/vslam/dso
5. DSO
· 论文：Engel J, Koltun V, Cremers D. Direct sparse odometry[J]. IEEE transactions on pattern analysis and machine intelligence, 2017, 40(3): 611-625.
· 代码：https://github.com/JakobEngel/dso
· 双目 DSO：Wang R, Schworer M, Cremers D. Stereo DSO: Large-scale direct sparse visual odometry with stereo cameras[C]//Proceedings of the IEEE International Conference on Computer Vision. 2017: 3903-3911.
· VI-DSO：Von Stumberg L, Usenko V, Cremers D. Direct sparse visual-inertial odometry using dynamic marginalization[C]//2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018: 2510-2517.
6. LDSO
· 高翔在 DSO 上添加闭环的工作
· 论文：Gao X, Wang R, Demmel N, et al. LDSO: Direct sparse odometry with loop closure[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 2198-2204.
· 代码：https://github.com/tum-vision/LDSO
7. LSD-SLAM
· 论文：Engel J, Schöps T, Cremers D. LSD-SLAM: Large-scale direct monocular SLAM[C]//European conference on computer vision. Springer, Cham, 2014: 834-849.
· 代码：https://github.com/tum-vision/lsd_slam
8. DVO-SLAM
· 论文：Kerl C, Sturm J, Cremers D. Dense visual SLAM for RGB-D cameras[C]//2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2013: 2100-2106.
· 代码 1：https://github.com/tum-vision/dvo_slam
· 代码 2：https://github.com/tum-vision/dvo
· 其他论文：
o Kerl C, Sturm J, Cremers D. Robust odometry estimation for RGB-D cameras[C]//2013 IEEE international conference on robotics and automation. IEEE, 2013: 3748-3754.
o Steinbrücker F, Sturm J, Cremers D. Real-time visual odometry from dense RGB-D images[C]//2011 IEEE international conference on computer vision workshops (ICCV Workshops). IEEE, 2011: 719-722.
9. SVO
· 苏黎世大学机器人与感知课题组
· 论文：Forster C, Pizzoli M, Scaramuzza D. SVO: Fast semi-direct monocular visual odometry[C]//2014 IEEE international conference on robotics and automation (ICRA). IEEE, 2014: 15-22.
· 代码：https://github.com/uzh-rpg/rpg_svo
· Forster C, Zhang Z, Gassner M, et al. SVO: Semidirect visual odometry for monocular and multicamera systems[J]. IEEE Transactions on Robotics, 2016, 33(2): 249-265.
10. DSM
· 论文：Zubizarreta J, Aguinaga I, Montiel J M M. Direct sparse mapping[J]. arXiv preprint arXiv:1904.06577, 2019.
· 代码：https://github.com/jzubizarreta/dsm ；Video
11. openvslam
· 论文：Sumikura S, Shibuya M, Sakurada K. OpenVSLAM: A Versatile Visual SLAM Framework[C]//Proceedings of the 27th ACM International Conference on Multimedia. 2019: 2292-2295.
· 代码：https://github.com/xdspacelab/openvslam ；文档
12. se2lam（地面车辆位姿估计的视觉里程计）
· 论文：Zheng F, Liu Y H. Visual-Odometric Localization and Mapping for Ground Vehicles Using SE (2)-XYZ Constraints[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 3556-3562.
· 代码：https://github.com/izhengfan/se2lam
· 作者的另外一项工作
o 论文：Zheng F, Tang H, Liu Y H. Odometry-vision-based ground vehicle motion estimation with se (2)-constrained se (3) poses[J]. IEEE transactions on cybernetics, 2018, 49(7): 2652-2663.
o 代码：https://github.com/izhengfan/se2clam
13. GraphSfM（基于图的并行大规模 SFM）
· 论文：Chen Y, Shen S, Chen Y, et al. Graph-Based Parallel Large Scale Structure from Motion[J]. arXiv preprint arXiv:1912.10659, 2019.
· 代码：https://github.com/AIBluefisher/GraphSfM
14. LCSD_SLAM（松耦合的半直接法单目 SLAM）
· 论文：Lee S H, Civera J. Loosely-Coupled semi-direct monocular SLAM[J]. IEEE Robotics and Automation Letters, 2018, 4(2): 399-406.
· 代码：https://github.com/sunghoon031/LCSD_SLAM ；谷歌学术；演示视频
· 作者另外一篇关于单目尺度的文章代码开源：Lee S H, de Croon G. Stability-based scale estimation for monocular SLAM[J]. IEEE Robotics and Automation Letters, 2018, 3(2): 780-787.
15. RESLAM（基于边的 SLAM）
· 论文：Schenk F, Fraundorfer F. RESLAM: A real-time robust edge-based SLAM system[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 154-160.
· 代码：https://github.com/fabianschenk/RESLAM ；项目主页
16. scale_optimization（将单目 DSO 拓展到双目）
· 论文：Mo J, Sattar J. Extending Monocular Visual Odometry to Stereo Camera System by Scale Optimization[C]. International Conference on Intelligent Robots and Systems (IROS), 2019.
· 代码：https://github.com/jiawei-mo/scale_optimization
17. BAD-SLAM（直接法 RGB-D SLAM）
· 论文：Schops T, Sattler T, Pollefeys M. BAD SLAM: Bundle Adjusted Direct RGB-D SLAM[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 134-144.
· 代码：https://github.com/ETH3D/badslam
18. GSLAM（集成 ORB-SLAM2，DSO，SVO 的通用框架）
· 论文：Zhao Y, Xu S, Bu S, et al. GSLAM: A general SLAM framework and benchmark[C]//Proceedings of the IEEE International Conference on Computer Vision. 2019: 1110-1120.
· 代码：https://github.com/zdzhaoyong/GSLAM
19. ARM-VO（运行于 ARM 处理器上的单目 VO）
· 论文：Nejad Z Z, Ahmadabadian A H. ARM-VO: an efficient monocular visual odometry for ground vehicles on ARM CPUs[J]. Machine Vision and Applications, 2019: 1-10.
· 代码：https://github.com/zanazakaryaie/ARM-VO
20. cvo-rgbd（直接法 RGB-D VO）
· 论文：Ghaffari M, Clark W, Bloch A, et al. Continuous Direct Sparse Visual Odometry from RGB-D Images[J]. arXiv preprint arXiv:1904.02266, 2019.
· 代码：https://github.com/MaaniGhaffari/cvo-rgbd
21. Map2DFusion（单目 SLAM 无人机图像拼接）
· 论文：Bu S, Zhao Y, Wan G, et al. Map2DFusion: Real-time incremental UAV image mosaicing based on monocular slam[C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016: 4564-4571.
· 代码：https://github.com/zdzhaoyong/Map2DFusion
22. CCM-SLAM（多机器人协同单目 SLAM）
· 论文：Schmuck P, Chli M. CCM‐SLAM: Robust and efficient centralized collaborative monocular simultaneous localization and mapping for robotic teams[J]. Journal of Field Robotics, 2019, 36(4): 763-781.
· 代码：https://github.com/VIS4ROB-lab/ccm_slam Video