X-SLAM

X-SLAM is an open source C++ demo for learn vision slam and lidar slam. Through open source engineering, we can learn the following knowledge content.

• C++ learning tutorial

• CMake learning tutorial

• Eigen learning tutorial

• OpenCV learning tutorial

• Quaternions learning tutorial

• Ceres Solver learning tutorial

• Kalman Filter learning tutorial

• VINS Mono(Project) learning tutorial(VIO)

• ORB SLAM(Project) learning tutorial(VIO)

• MSCKF-VIO(Project) learning tutorial(VO)

• LSD-SLAM(Project) learning tutorial(VIO)

• Cartographer(Project) learning tutorial(lidar SLAM)

• BALM(Project) learning tutorial(lidar SLAM)

QQ开源社区

SLAM Research

1.开源代码

1.1 Geometric SLAM

1. PTAM

   • 论文：Klein G, Murray D. [Parallel tracking and mapping for small AR workspaces](http://www.robots.ox.ac.uk/ActiveVision/Publications/klein_murray_ismar2007/klein_murray_ismar2007.pdf)[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](http://webdiis.unizar.es/~jcivera/papers/pire_etal_ras17.pdf). 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](https://www.researchgate.net/profile/Gaston_Castro/publication/332147108_Efficient_on-board_Stereo_SLAM_through_constrained-covisibility_strategies/links/5cacb327a6fdccfa0e7c3e4b/Efficient-on-board-Stereo-SLAM-through-constrained-covisibility-strategies.pdf)[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](https://ieeexplore.ieee.org/abstract/document/4160954/)[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](https://github.com/raulmur/ORB_SLAM2)[J]. IEEE Transactions on Robotics, 2017, 33(5): 1255-1262.

   • 代码：https://github.com/raulmur/ORB_SLAM2

   • 作者其他论文：

     • 单目半稠密建图：Mur-Artal R, Tardós J D. [Probabilistic Semi-Dense Mapping from Highly Accurate Feature-Based Monocular SLAM](https://www.researchgate.net/profile/Raul_Mur-Artal/publication/282807894_Probabilistic_Semi-Dense_Mapping_from_Highly_Accurate_Feature-Based_Monocular_SLAM/links/561cd04308ae6d17308ce267.pdf)[C]//Robotics: Science and Systems. 2015, 2015.

     • VIORB：Mur-Artal R, Tardós J D. [Visual-inertial monocular SLAM with map reuse](https://arxiv.org/pdf/1610.05949.pdf)[J]. IEEE Robotics and Automation Letters, 2017, 2(2): 796-803.

     • 多地图：Elvira R, Tardós J D, Montiel J M M. [ORBSLAM-Atlas: a robust and accurate multi-map system](https://arxiv.org/pdf/1908.11585)[J]. arXiv preprint arXiv:1908.11585, 2019.

5. DSO

   • 论文：Engel J, Koltun V, Cremers D. [Direct sparse odometry](https://ieeexplore.ieee.org/iel7/34/4359286/07898369.pdf)[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](http://openaccess.thecvf.com/content_ICCV_2017/papers/Wang_Stereo_DSO_Large-Scale_ICCV_2017_paper.pdf)[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](https://arxiv.org/pdf/1804.05625)[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](https://arxiv.org/pdf/1808.01111)[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](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.646.7193&rep=rep1&type=pdf)[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：

     • Kerl C, Sturm J, Cremers D. [Robust odometry estimation for RGB-D cameras](https://vision.in.tum.de/_media/spezial/bib/kerl13icra.pdf)[C]//2013 IEEE international conference on robotics and automation. IEEE, 2013: 3748-3754.

     • Steinbrücker F, Sturm J, Cremers D. [Real-time visual odometry from dense RGB-D images](https://jsturm.de/publications/data/steinbruecker_sturm_cremers_iccv11.pdf)[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](http://rpg.ifi.uzh.ch/publications.html)

   • 论文：Forster C, Pizzoli M, Scaramuzza D. [SVO: Fast semi-direct monocular visual odometry](https://www.zora.uzh.ch/id/eprint/125453/1/ICRA14_Forster.pdf)[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](https://www.zora.uzh.ch/id/eprint/127902/1/TRO16_Forster-SVO.pdf)[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](https://arxiv.org/pdf/1904.06577)[J]. arXiv preprint arXiv:1904.06577, 2019.

• 代码：https://github.com/jzubizarreta/dsm ；[Video](https://www.youtube.com/watch?v=sj1GIF-7BYo&feature=youtu.be)

11. openvslam

• 论文：Sumikura S, Shibuya M, Sakurada K. [OpenVSLAM: A Versatile Visual SLAM Framework](https://dl.acm.org/ft_gateway.cfm?id=3350539&type=pdf)[C]//Proceedings of the 27th ACM International Conference on Multimedia. 2019: 2292-2295.

• 代码：https://github.com/xdspacelab/openvslam ；[文档](https://openvslam.readthedocs.io/en/master/)

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](https://ieeexplore.ieee.org/abstract/document/8793928)[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

  • 论文：Zheng F, Tang H, Liu Y H. [Odometry-vision-based ground vehicle motion estimation with se (2)-constrained se (3) poses](https://ieeexplore.ieee.org/abstract/document/8357438/)[J]. IEEE transactions on cybernetics, 2018, 49(7): 2652-2663.

  • 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](https://arxiv.org/pdf/1912.10659.pdf)[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](https://arxiv.org/pdf/1807.10073)[J]. IEEE Robotics and Automation Letters, 2018, 4(2): 399-406.

• 代码：https://github.com/sunghoon031/LCSD_SLAM ；[谷歌学术](https://scholar.google.com/citations?user=FeMFP7EAAAAJ&hl=zh-CN&oi=sra) ；[演示视频](https://www.youtube.com/watch?v=j7WnU7ZpZ8c&feature=youtu.be)

• 作者另外一篇关于**单目尺度**的文章 [代码开源](https://github.com/sunghoon031/stability_scale) ：Lee S H, de Croon G. [Stability-based scale estimation for monocular SLAM](https://www.researchgate.net/profile/Seong_Hun_Lee3/publication/322260802_Stability-based_Scale_Estimation_for_Monocular_SLAM/links/5b3def9b0f7e9b0df5f42d67/Stability-based-Scale-Estimation-for-Monocular-SLAM.pdf)[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](https://ieeexplore.ieee.org/abstract/document/8794462/)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 154-160.

• 代码：https://github.com/fabianschenk/RESLAM ； [项目主页](https://graz.pure.elsevier.com/en/publications/reslam-a-real-time-robust-edge-based-slam-system)

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](https://arxiv.org/pdf/1905.12723.pdf)[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](http://openaccess.thecvf.com/content_CVPR_2019/papers/Schops_BAD_SLAM_Bundle_Adjusted_Direct_RGB-D_SLAM_CVPR_2019_paper.pdf)[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](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zhao_GSLAM_A_General_SLAM_Framework_and_Benchmark_ICCV_2019_paper.pdf)[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](https://link.springer.com/article/10.1007/s00138-019-01037-5)[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](https://arxiv.org/pdf/1904.02266.pdf)[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](http://www.adv-ci.com/publications/2016_IROS.pdf)[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](https://onlinelibrary.wiley.com/doi/abs/10.1002/rob.21854)[J]. Journal of Field Robotics, 2019, 36(4): 763-781.

• 代码：https://github.com/VIS4ROB-lab/ccm_slam   [Video](https://www.youtube.com/watch?v=P3b7UiTlmbQ&feature=youtu.be)

23. ORB-SLAM3

• 论文：Carlos Campos, Richard Elvira, et al.[ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM](https://arxiv.org/abs/2007.11898)[J]. arXiv preprint arXiv:2007.11898, 2020.

• 代码：https://github.com/UZ-SLAMLab/ORB_SLAM3 | [Video](https://www.youtube.com/channel/UCXVt-kXG6T95Z4tVaYlU80Q)

24. OV²SLAM（完全实时在线多功能 SLAM）

• 论文：Ferrera M, Eudes A, Moras J, et al. [OV $^{2} $ SLAM: A Fully Online and Versatile Visual SLAM for Real-Time Applications](https://ieeexplore.ieee.org/abstract/document/9351614/)[J]. IEEE Robotics and Automation Letters, 2021, 6(2): 1399-1406.

• 代码：https://github.com/ov2slam/ov2slam

25. ESVO（基于事件的双目视觉里程计）

• 论文：Zhou Y, Gallego G, Shen S. [Event-based stereo visual odometry](https://ieeexplore.ieee.org/abstract/document/9386209/)[J]. IEEE Transactions on Robotics, 2021.

• 代码：https://github.com/HKUST-Aerial-Robotics/ESVO

26. VOLDOR-SLAM（实时稠密非直接法 SLAM）

• 论文：Min Z, Dunn E. [VOLDOR-SLAM: For the Times When Feature-Based or Direct Methods Are Not Good Enough](https://arxiv.org/abs/2104.06800)[J]. arXiv preprint arXiv:2104.06800, 2021.

• 代码：https://github.com/htkseason/VOLDOR

1.2 Semantic / Deep SLAM

1. MsakFusion

   • 论文：Runz M, Buffier M, Agapito L. [Maskfusion: Real-time recognition, tracking and reconstruction of multiple moving objects](https://arxiv.org/pdf/1804.09194)[C]//2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE, 2018: 10-20.

   • 代码：https://github.com/martinruenz/maskfusion

2. SemanticFusion

   • 论文：McCormac J, Handa A, Davison A, et al. [Semanticfusion: Dense 3d semantic mapping with convolutional neural networks](https://arxiv.org/pdf/1609.05130.pdf)[C]//2017 IEEE International Conference on Robotics and automation (ICRA). IEEE, 2017: 4628-4635.

   • 代码：https://github.com/seaun163/semanticfusion

3. semantic_3d_mapping

   • 论文：Yang S, Huang Y, Scherer S. [Semantic 3D occupancy mapping through efficient high order CRFs](https://arxiv.org/pdf/1707.07388.pdf)[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017: 590-597.

   • 代码：https://github.com/shichaoy/semantic_3d_mapping

4. Kimera（实时度量与语义定位建图开源库）

   • 论文：Rosinol A, Abate M, Chang Y, et al. [Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping](https://arxiv.org/pdf/1910.02490.pdf)[J]. arXiv preprint arXiv:1910.02490, 2019.

   • 代码：https://github.com/MIT-SPARK/Kimera ；[演示视频](https://www.youtube.com/watch?v=3lVD0i-5p10)

5. NeuroSLAM（脑启发式 SLAM）

   • 论文：Yu F, Shang J, Hu Y, et al. [NeuroSLAM: a brain-inspired SLAM system for 3D environments](https://www.researchgate.net/profile/Fangwen_Yu/publication/336164484_NeuroSLAM_a_brain-inspired_SLAM_system_for_3D_environments/links/5d95f38d458515c1d3908a20/NeuroSLAM-a-brain-inspired-SLAM-system-for-3D-environments.pdf)[J]. Biological Cybernetics, 2019: 1-31.

   • 代码：https://github.com/cognav/NeuroSLAM

   • 第四作者就是 Rat SLAM 的作者，文章也比较了十余种脑启发式的 SLAM

6. gradSLAM（自动分区的稠密 SLAM）

   • 论文：Jatavallabhula K M, Iyer G, Paull L. [gradSLAM: Dense SLAM meets Automatic Differentiation](https://arxiv.org/pdf/1910.10672.pdf)[J]. arXiv preprint arXiv:1910.10672, 2019.

   • **代码**（预计 20 年 4 月放出）：https://github.com/montrealrobotics/gradSLAM ；[项目主页](http://montrealrobotics.ca/gradSLAM/)，[演示视频](https://www.youtube.com/watch?v=2ygtSJTmo08&feature=youtu.be)

7. ORB-SLAM2 + 目标检测/分割的方案语义建图

   • https://github.com/floatlazer/semantic_slam

   • https://github.com/qixuxiang/orb-slam2_with_semantic_labelling

   • https://github.com/Ewenwan/ORB_SLAM2_SSD_Semantic

8. SIVO（语义辅助特征选择）

   • 论文：Ganti P, Waslander S. [Network Uncertainty Informed Semantic Feature Selection for Visual SLAM](https://ieeexplore.ieee.org/abstract/document/8781616)[C]//2019 16th Conference on Computer and Robot Vision (CRV). IEEE, 2019: 121-128.

   • 代码：https://github.com/navganti/SIVO

9. FILD（临近图增量式闭环检测）

   • 论文：Shan An, Guangfu Che, Fangru Zhou, Xianglong Liu, Xin Ma, Yu Chen.[ Fast and Incremental Loop Closure Detection using Proximity Graphs](https://arxiv.org/pdf/1911.10752.pdf). pp. 378-385, The 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019)

   • 代码：https://github.com/AnshanTJU/FILD

10. object-detection-sptam（目标检测与双目 SLAM）

• 论文：Pire T, Corti J, Grinblat G. [Online Object Detection and Localization on Stereo Visual SLAM System](https://www.researchgate.net/profile/Taihu_Pire/publication/335432416_Online_Object_Detection_and_Localization_on_Stereo_Visual_SLAM_System/links/5d663a14a6fdccf343f93830/Online-Object-Detection-and-Localization-on-Stereo-Visual-SLAM-System.pdf)[J]. Journal of Intelligent & Robotic Systems, 2019: 1-10.

• 代码：https://github.com/CIFASIS/object-detection-sptam

11. Map Slammer（单目深度估计 + SLAM）

• 论文：Torres-Camara J M, Escalona F, Gomez-Donoso F, et al. [Map Slammer: Densifying Scattered KSLAM 3D Maps with Estimated Depth](https://link.springer.com/chapter/10.1007/978-3-030-36150-1_46)[C]//Iberian Robotics conference. Springer, Cham, 2019: 563-574.

• 代码：https://github.com/jmtc7/mapSlammer

12. NOLBO（变分模型的概率 SLAM）

• 论文：Yu H, Lee B. [Not Only Look But Observe: Variational Observation Model of Scene-Level 3D Multi-Object Understanding for Probabilistic SLAM](https://arxiv.org/pdf/1907.09760.pdf)[J]. arXiv preprint arXiv:1907.09760, 2019.

• 代码：https://github.com/bogus2000/NOLBO

13. GCNv2_SLAM （基于图卷积神经网络 SLAM）

• 论文：Tang J, Ericson L, Folkesson J, et al. [GCNv2: Efficient correspondence prediction for real-time SLAM](https://ieeexplore.ieee.org/abstract/document/8758836/)[J]. IEEE Robotics and Automation Letters, 2019, 4(4): 3505-3512.

• 代码：https://github.com/jiexiong2016/GCNv2_SLAM   [Video](https://www.youtube.com/watch?v=pz-gdnR9tAM)

14. semantic_suma（激光语义建图）

• 论文：Chen X, Milioto A, Palazzolo E, et al. [SuMa++: Efficient LiDAR-based semantic SLAM](https://ieeexplore.ieee.org/abstract/document/8967704/)[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019: 4530-4537.

• 代码：https://github.com/PRBonn/semantic_suma/ ；[Video](https://www.youtube.com/watch?v=uo3ZuLuFAzk&feature=youtu.be)

15. Neural-SLAM（主动神经 SLAM）

• 论文：Chaplot D S, Gandhi D, Gupta S, et al. [Learning to explore using active neural slam](https://arxiv.org/abs/2004.05155)[C]. ICLR 2020.

• 代码：https://github.com/devendrachaplot/Neural-SLAM

16. TartanVO：一种通用的基于学习的 VO

• 论文：Wang W, Hu Y, Scherer S. [TartanVO: A Generalizable Learning-based VO](https://arxiv.org/abs/2011.00359)[J]. arXiv preprint arXiv:2011.00359, 2020.

• 代码：https://github.com/castacks/tartanvo

• 数据集：IROS2020 [TartanAir: A Dataset to Push the Limits of Visual SLAM](https://arxiv.org/abs/2003.14338)，[数据集地址](http://theairlab.org/tartanair-dataset/)

17. DF-VO

• 论文：Zhan H, Weerasekera C S, Bian J W, et al. [DF-VO: What Should Be Learnt for Visual Odometry?](https://arxiv.org/abs/2103.00933)[J]. arXiv preprint arXiv:2103.00933, 2021.

• Zhan H, Weerasekera C S, Bian J W, et al. [Visual odometry revisited: What should be learnt?](https://ieeexplore.ieee.org/abstract/document/9197374/)[C]//2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2020: 4203-4210.

• 代码：https://github.com/Huangying-Zhan/DF-VO

1.3 Multi-Landmarks / Object SLAM

1. PL-SVO（点线 SVO）

   • 论文：Gomez-Ojeda R, Briales J, Gonzalez-Jimenez J. [PL-SVO: Semi-direct Monocular Visual Odometry by combining points and line segments](http://mapir.isa.uma.es/rgomez/publications/iros16plsvo.pdf)[C]//Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on. IEEE, 2016: 4211-4216.

   • 代码：https://github.com/rubengooj/pl-svo

2. stvo-pl（双目点线 VO）

   • 论文：Gomez-Ojeda R, Gonzalez-Jimenez J. [Robust stereo visual odometry through a probabilistic combination of points and line segments](https://riuma.uma.es/xmlui/bitstream/handle/10630/11515/icra16rgo.pdf?sequence=1&isAllowed=y)[C]//2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2016: 2521-2526.

   • 代码：https://github.com/rubengooj/stvo-pl

3. PL-SLAM（点线 SLAM）

   • 论文：Gomez-Ojeda R, Zuñiga-Noël D, Moreno F A, et al. [PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments](https://arxiv.org/pdf/1705.09479.pdf)[J]. arXiv preprint arXiv:1705.09479, 2017.

   • 代码：https://github.com/rubengooj/pl-slam

   • Gomez-Ojeda R, Moreno F A, Zuñiga-Noël D, et al. [PL-SLAM: a stereo SLAM system through the combination of points and line segments](https://arxiv.org/pdf/1705.09479)[J]. IEEE Transactions on Robotics, 2019, 35(3): 734-746.

4. PL-VIO

   • 论文：He Y, Zhao J, Guo Y, et al. [PL-VIO: Tightly-coupled monocular visual–inertial odometry using point and line features](https://www.mdpi.com/1424-8220/18/4/1159)[J]. Sensors, 2018, 18(4): 1159.

   • 代码：https://github.com/HeYijia/PL-VIO

   • VINS + 线段：https://github.com/Jichao-Peng/VINS-Mono-Optimization

5. lld-slam（用于 SLAM 的可学习型线段描述符）

   • 论文：Vakhitov A, Lempitsky V. [Learnable line segment descriptor for visual SLAM](https://ieeexplore.ieee.org/iel7/6287639/6514899/08651490.pdf)[J]. IEEE Access, 2019, 7: 39923-39934.

   • 代码：https://github.com/alexandervakhitov/lld-slam ；[Video](https://www.youtube.com/watch?v=ntFFiwXIhoA)

   点线结合的工作还有很多，国内的比如

   • 上交邹丹平老师的 Zou D, Wu Y, Pei L, et al. [StructVIO: visual-inertial odometry with structural regularity of man-made environments](https://arxiv.org/pdf/1810.06796)[J]. IEEE Transactions on Robotics, 2019, 35(4): 999-1013.

   • 浙大的 Zuo X, Xie X, Liu Y, et al. [Robust visual SLAM with point and line features](https://arxiv.org/pdf/1711.08654)[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017: 1775-1782.</small>

6. PlaneSLAM

   • 论文：Wietrzykowski J. [On the representation of planes for efficient graph-based slam with high-level features](https://yadda.icm.edu.pl/baztech/element/bwmeta1.element.baztech-7ac7a8f3-9caa-4a34-8a27-8f6c5f43408b)[J]. Journal of Automation Mobile Robotics and Intelligent Systems, 2016, 10.

   • 代码：https://github.com/LRMPUT/PlaneSLAM

   • 作者另外一项开源代码，没有找到对应的论文：https://github.com/LRMPUT/PUTSLAM

7. Eigen-Factors（特征因子平面对齐）

   • 论文：Ferrer G. [Eigen-Factors: Plane Estimation for Multi-Frame and Time-Continuous Point Cloud Alignment](http://sites.skoltech.ru/app/data/uploads/sites/50/2019/07/ferrer2019planes.pdf)[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019: 1278-1284.

   • 代码：https://gitlab.com/gferrer/eigen-factors-iros2019 ；[演示视频](https://www.youtube.com/watch?v=_1u_c43DFUE&feature=youtu.be)

8. PlaneLoc

   • 论文：Wietrzykowski J, Skrzypczyński P. [PlaneLoc: Probabilistic global localization in 3-D using local planar features]()[J]. Robotics and Autonomous Systems, 2019, 113: 160-173.

   • 代码：https://github.com/LRMPUT/PlaneLoc

9. Pop-up SLAM

   • 论文：Yang S, Song Y, Kaess M, et al. [Pop-up slam: Semantic monocular plane slam for low-texture environments](https://arxiv.org/pdf/1703.07334.pdf)[C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016: 1222-1229.

   • 代码：https://github.com/shichaoy/pop_up_slam

10. Object SLAM

• 论文：Mu B, Liu S Y, Paull L, et al. [Slam with objects using a nonparametric pose graph](https://arxiv.org/pdf/1704.05959.pdf)[C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016: 4602-4609.

• 代码：https://github.com/BeipengMu/objectSLAM ；[Video](https://www.youtube.com/watch?v=YANUWdVLJD4&feature=youtu.be)

11. voxblox-plusplus（物体级体素建图）

• 论文：Grinvald M, Furrer F, Novkovic T, et al. [Volumetric instance-aware semantic mapping and 3D object discovery](https://arxiv.org/pdf/1903.00268.pdf)[J]. IEEE Robotics and Automation Letters, 2019, 4(3): 3037-3044.

• 代码：https://github.com/ethz-asl/voxblox-plusplus

12. Cube SLAM

• 论文：Yang S, Scherer S. [Cubeslam: Monocular 3-d object slam](https://arxiv.org/pdf/1806.00557)[J]. IEEE Transactions on Robotics, 2019, 35(4): 925-938.

• 代码：https://github.com/shichaoy/cube_slam

• 对，这就是带我入坑的一项工作，2018 年 11 月份看到这篇论文（当时是预印版）之后开始学习物体级 SLAM，个人对 Cube SLAM 的一些注释和总结：[链接](https://wym.netlify.app/categories/cube-slam/)。

• 也有很多有意思的但没开源的物体级 SLAM

  • Ok K, Liu K, Frey K, et al. [Robust Object-based SLAM for High-speed Autonomous Navigation](http://groups.csail.mit.edu/rrg/papers/OkLiu19icra.pdf)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 669-675.

  • Li J, Meger D, Dudek G. [Semantic Mapping for View-Invariant Relocalization](https://www.cim.mcgill.ca/~mrl/pubs/jimmy/li2019icra.pdf)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 7108-7115.

  • Nicholson L, Milford M, Sünderhauf N. [Quadricslam: Dual quadrics from object detections as landmarks in object-oriented slam](https://arxiv.org/pdf/1804.04011)[J]. IEEE Robotics and Automation Letters, 2018, 4(1): 1-8.

13. VPS-SLAM（平面语义 SLAM）

• 论文：Bavle H, De La Puente P, How J, et al. [VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems](https://ieeexplore.ieee.org/iel7/6287639/8948470/09045978.pdf)[J]. IEEE Access, 2020.

• 代码：https://bitbucket.org/hridaybavle/semantic_slam/src/master/

14. Structure-SLAM （低纹理环境下点线 SLAM）

• 论文：Li Y, Brasch N, Wang Y, et al. [Structure-SLAM: Low-Drift Monocular SLAM in Indoor Environments](https://ieeexplore.ieee.org/abstract/document/9165014)[J]. IEEE Robotics and Automation Letters, 2020, 5(4): 6583-6590.

• 代码：https://github.com/yanyan-li/Structure-SLAM-PointLine

15. PL-VINS

• 论文：Fu Q, Wang J, Yu H, et al. [PL-VINS: Real-Time Monocular Visual-Inertial SLAM with Point and Line](https://arxiv.org/abs/2009.07462)[J]. arXiv preprint arXiv:2009.07462, 2020.

• 代码：https://github.com/cnqiangfu/PL-VINS

1.4 Sensor Fusion

1. msckf_vio

   • 论文：Sun K, Mohta K, Pfrommer B, et al. [Robust stereo visual inertial odometry for fast autonomous flight](https://arxiv.org/pdf/1712.00036)[J]. IEEE Robotics and Automation Letters, 2018, 3(2): 965-972.

   • 代码：https://github.com/KumarRobotics/msckf_vio ；[Video](https://www.youtube.com/watch?v=jxfJFgzmNSw&t)

2. rovio

   • 论文：Bloesch M, Omari S, Hutter M, et al. [Robust visual inertial odometry using a direct EKF-based approach](https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/155340/1/eth-48374-01.pdf)[C]//2015 IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, 2015: 298-304.

   • 代码：https://github.com/ethz-asl/rovio ；[Video](https://www.youtube.com/watch?v=ZMAISVy-6ao&feature=youtu.be)

3. R-VIO

   • 论文：Huai Z, Huang G. [Robocentric visual-inertial odometry](https://arxiv.org/pdf/1805.04031)[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 6319-6326.

   • 代码：https://github.com/rpng/R-VIO ；[Video](https://www.youtube.com/watch?v=l9IC2ddBEYQ)

   • VI_ORB_SLAM2：https://github.com/YoujieXia/VI_ORB_SLAM2

4. okvis

   • 论文：Leutenegger S, Lynen S, Bosse M, et al. [Keyframe-based visual–inertial odometry using nonlinear optimization](https://spiral.imperial.ac.uk/bitstream/10044/1/23413/2/ijrr2014_revision_1.pdf)[J]. The International Journal of Robotics Research, 2015, 34(3): 314-334.

   • 代码：https://github.com/ethz-asl/okvis

5. VIORB

   • 论文：Mur-Artal R, Tardós J D. [Visual-inertial monocular SLAM with map reuse](https://arxiv.org/pdf/1610.05949.pdf)[J]. IEEE Robotics and Automation Letters, 2017, 2(2): 796-803.

   • 代码：https://github.com/jingpang/LearnVIORB （VIORB 本身是没有开源的，这是王京大佬复现的一个版本）

6. VINS-mono

   • 论文：Qin T, Li P, Shen S. [Vins-mono: A robust and versatile monocular visual-inertial state estimator](https://arxiv.org/pdf/1708.03852)[J]. IEEE Transactions on Robotics, 2018, 34(4): 1004-1020.

   • 代码：https://github.com/HKUST-Aerial-Robotics/VINS-Mono

   • 双目版 VINS-Fusion：https://github.com/HKUST-Aerial-Robotics/VINS-Fusion

   • 移动段 VINS-mobile：https://github.com/HKUST-Aerial-Robotics/VINS-Mobile

7. VINS-RGBD

   • 论文：Shan Z, Li R, Schwertfeger S. [RGBD-Inertial Trajectory Estimation and Mapping for Ground Robots](https://www.mdpi.com/1424-8220/19/10/2251)[J]. Sensors, 2019, 19(10): 2251.

   • 代码：https://github.com/STAR-Center/VINS-RGBD ；[Video](https://robotics.shanghaitech.edu.cn/datasets/VINS-RGBD)

8. Open-VINS

   • 论文：Geneva P, Eckenhoff K, Lee W, et al. [Openvins: A research platform for visual-inertial estimation](https://pdfs.semanticscholar.org/cb63/60f21255834297e32826bff6366a769b49e9.pdf)[C]//IROS 2019 Workshop on Visual-Inertial Navigation: Challenges and Applications, Macau, China. IROS 2019.

   • 代码：https://github.com/rpng/open_vins

9. versavis（多功能的视惯传感器系统）

   • 论文：Tschopp F, Riner M, Fehr M, et al. [VersaVIS—An Open Versatile Multi-Camera Visual-Inertial Sensor Suite](https://www.mdpi.com/1424-8220/20/5/1439)[J]. Sensors, 2020, 20(5): 1439.

   • 代码：https://github.com/ethz-asl/versavis

10. CPI（视惯融合的封闭式预积分）

• 论文：Eckenhoff K, Geneva P, Huang G. [Closed-form preintegration methods for graph-based visual–inertial navigation](http://sage.cnpereading.com/paragraph/article/10.1177/0278364919835021)[J]. The International Journal of Robotics Research, 2018.

• 代码：https://github.com/rpng/cpi ；[Video](https://www.youtube.com/watch?v=yIgQX2SH_pI)

11. TUM Basalt

• 论文：Usenko V, Demmel N, Schubert D, et al. [Visual-inertial mapping with non-linear factor recovery](https://link.zhihu.com/?target=https%3A//arxiv.org/pdf/1904.06504.pdf)[J]. IEEE Robotics and Automation Letters, 2019.

• 代码：[https://github.com/VladyslavUsenko/basalt-mirror](https://link.zhihu.com/?target=https%3A//github.com/VladyslavUsenko/basalt-mirror) ；[Video](https://link.zhihu.com/?target=https%3A//www.youtube.com/watch%3Fv%3Dr3CJ2JP75Tc)；[Project Page](https://link.zhihu.com/?target=https%3A//vision.in.tum.de/research/vslam/basalt)

12. Limo（激光单目视觉里程计）

• 论文：Graeter J, Wilczynski A, Lauer M. [Limo: Lidar-monocular visual odometry](https://arxiv.org/pdf/1807.07524)[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 7872-7879.

• 代码：https://github.com/johannes-graeter/limo ； [Video](https://www.youtube.com/watch?v=wRemjJBjp64&feature=youtu.be)

13. LARVIO（多状态约束卡尔曼滤波的单目 VIO）

• 论文：Qiu X, Zhang H, Fu W, et al. [Monocular Visual-Inertial Odometry with an Unbiased Linear System Model and Robust Feature Tracking Front-End](https://www.mdpi.com/1424-8220/19/8/1941)[J]. Sensors, 2019, 19(8): 1941.

• 代码：https://github.com/PetWorm/LARVIO

• 北航邱笑晨博士的一项工作

14. vig-init（垂直边缘加速视惯初始化）

• 论文：Li J, Bao H, Zhang G. [Rapid and Robust Monocular Visual-Inertial Initialization with Gravity Estimation via Vertical Edges](http://www.cad.zju.edu.cn/home/gfzhang/projects/iros2019-vi-initialization.pdf)[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019: 6230-6236.

• 代码：https://github.com/zju3dv/vig-init

• 浙大章国峰老师组的一项工作

15. vilib（VIO 前端库）

• 论文：Nagy B, Foehn P, Scaramuzza D. [Faster than FAST: GPU-Accelerated Frontend for High-Speed VIO](https://arxiv.org/pdf/2003.13493)[J]. arXiv preprint arXiv:2003.13493, 2020.

• 代码：https://github.com/uzh-rpg/vilib

16. Kimera-VIO

• 论文：A. Rosinol, M. Abate, Y. Chang, L. Carlone, [Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping](https://arxiv.org/abs/1910.02490). IEEE Intl. Conf. on Robotics and Automation (ICRA), 2020.

• 代码：https://github.com/MIT-SPARK/Kimera-VIO

17. maplab（视惯建图框架）

• 论文：Schneider T, Dymczyk M, Fehr M, et al. [maplab: An open framework for research in visual-inertial mapping and localization](https://arxiv.org/pdf/1711.10250)[J]. IEEE Robotics and Automation Letters, 2018, 3(3): 1418-1425.

• 代码：https://github.com/ethz-asl/maplab

• 多会话建图，地图合并，视觉惯性批处理优化和闭环

18. lili-om：固态雷达惯性里程计与建图

• 论文：Li K, Li M, Hanebeck U D. [Towards high-performance solid-state-lidar-inertial odometry and mapping](https://arxiv.org/abs/2010.13150)[J]. arXiv preprint arXiv:2010.13150, 2020.

• 代码：https://github.com/KIT-ISAS/lili-om

19. CamVox：Lidar 辅助视觉 SLAM

• 论文：ZHU, Yuewen, et al. [CamVox: A Low-cost and Accurate Lidar-assisted Visual SLAM System](https://arxiv.org/abs/2011.11357). arXiv preprint arXiv:2011.11357, 2020.

• 代码：https://github.com/ISEE-Technology/CamVox

20. SSL_SLAM：固态 LiDAR 轻量级 3D 定位与建图

• 论文：Wang H, Wang C, Xie L. [Lightweight 3-D Localization and Mapping for Solid-State LiDAR](https://ieeexplore.ieee.org/abstract/document/9357899)[J]. IEEE Robotics and Automation Letters, 2021, 6(2): 1801-1807.

• 代码：https://github.com/wh200720041/SSL_SLAM

21. r2live：LiDAR-Inertial-Visual 紧耦合

• 论文：Lin J, Zheng C, Xu W, et al. [R2LIVE: A Robust, Real-time, LiDAR-Inertial-Visual tightly-coupled state Estimator and mapping](https://arxiv.org/abs/2102.12400)[J]. arXiv preprint arXiv:2102.12400, 2021.

• 代码：https://github.com/hku-mars/r2live

22. GVINS：GNSS-视觉-惯导紧耦合

• 论文：Cao S, Lu X, Shen S. [GVINS: Tightly Coupled GNSS-Visual-Inertial for Smooth and Consistent State Estimation](https://ui.adsabs.harvard.edu/abs/2021arXiv210307899C/abstract)[J]. arXiv e-prints, 2021: arXiv: 2103.07899.

• 代码：https://github.com/HKUST-Aerial-Robotics/GVINS

23. LVI-SAM：Lidar-Visual-Inertial 建图与定位

• 论文：Shan T, Englot B, Ratti C, et al. [LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping](https://arxiv.org/abs/2104.10831)[J]. arXiv preprint arXiv:2104.10831, 2021. (ICRA2021)

• 代码：https://github.com/TixiaoShan/LVI-SAM

1.5 Dynamic SLAM

1. DynamicSemanticMapping（动态语义建图）

   • 论文：Kochanov D, Ošep A, Stückler J, et al. [Scene flow propagation for semantic mapping and object discovery in dynamic street scenes](http://web-info8.informatik.rwth-aachen.de/media/papers/paper_compressed.pdf)[C]//Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on. IEEE, 2016: 1785-1792.

   • 代码：https://github.com/ganlumomo/DynamicSemanticMapping ；[wiki](https://github.com/ganlumomo/DynamicSemanticMapping/wiki)

2. DS-SLAM（动态语义 SLAM）

   • 论文：Yu C, Liu Z, Liu X J, et al. [DS-SLAM: A semantic visual SLAM towards dynamic environments](https://arxiv.org/pdf/1809.08379)[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 1168-1174.

   • 代码：https://github.com/ivipsourcecode/DS-SLAM

3. Co-Fusion（实时分割与跟踪多物体）

   • 论文：Rünz M, Agapito L. [Co-fusion: Real-time segmentation, tracking and fusion of multiple objects](https://ieeexplore.ieee.org/abstract/document/7989518)[C]//2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2017: 4471-4478.

   • 代码：https://github.com/martinruenz/co-fusion ； [Video](http://visual.cs.ucl.ac.uk/pubs/cofusion/index.html)

4. DynamicFusion

   • 论文：Newcombe R A, Fox D, Seitz S M. [Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Newcombe_DynamicFusion_Reconstruction_and_2015_CVPR_paper.pdf)[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2015: 343-352.

   • 代码：https://github.com/mihaibujanca/dynamicfusion

5. ReFusion（动态场景利用残差三维重建）

   • 论文：Palazzolo E, Behley J, Lottes P, et al. [ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residuals](https://arxiv.org/pdf/1905.02082.pdf)[J]. arXiv preprint arXiv:1905.02082, 2019.

   • 代码：https://github.com/PRBonn/refusion ；[Video](https://www.youtube.com/watch?v=1P9ZfIS5-p4&feature=youtu.be)

6. DynSLAM（室外大规模稠密重建）

   • 论文：Bârsan I A, Liu P, Pollefeys M, et al. [Robust dense mapping for large-scale dynamic environments](https://arxiv.org/pdf/1905.02781.pdf?utm_term)[C]//2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018: 7510-7517.

   • 代码：https://github.com/AndreiBarsan/DynSLAM

   • 作者博士学位论文：Barsan I A. [Simultaneous localization and mapping in dynamic scenes](https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/202829/1/Barsan_Ioan.pdf)[D]. ETH Zurich, Department of Computer Science, 2017.

7. VDO-SLAM（动态物体感知的 SLAM）

   • 论文：Zhang J, Henein M, Mahony R, et al. [VDO-SLAM: A Visual Dynamic Object-aware SLAM System](https://arxiv.org/abs/2005.11052)[J]. arXiv preprint arXiv:2005.11052, 2020.（IJRR Under Review）

     • 相关论文

       • IROS 2020 [Robust Ego and Object 6-DoF Motion Estimation and Tracking](https://arxiv.org/abs/2007.13993)

       • ICRA 2020 [Dynamic SLAM: The Need For Speed](https://arxiv.org/abs/2002.08584)

   代码：https://github.com/halajun/VDO_SLAM | [video](https://drive.google.com/file/d/1PbL4KiJ3sUhxyJSQPZmRP6mgi9dIC0iu/view)

1.6 Mapping

1. InfiniTAM（跨平台 CPU 实时重建）

   • 论文：Prisacariu V A, Kähler O, Golodetz S, et al. [Infinitam v3: A framework for large-scale 3d reconstruction with loop closure](https://arxiv.org/pdf/1708.00783)[J]. arXiv preprint arXiv:1708.00783, 2017.

   • 代码：https://github.com/victorprad/InfiniTAM ；[project page](http://www.robots.ox.ac.uk/~victor/infinitam/)

2. BundleFusion

   • 论文：Dai A, Nießner M, Zollhöfer M, et al. [Bundlefusion: Real-time globally consistent 3d reconstruction using on-the-fly surface reintegration](https://arxiv.org/pdf/1604.01093.pdf)[J]. ACM Transactions on Graphics (TOG), 2017, 36(4): 76a.

   • 代码：https://github.com/niessner/BundleFusion ；[工程地址](http://graphics.stanford.edu/projects/bundlefusion/)

3. KinectFusion

   • 论文：Newcombe R A, Izadi S, Hilliges O, et al. [KinectFusion: Real-time dense surface mapping and tracking](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/kinectfusion-uist-comp.pdf)[C]//2011 10th IEEE International Symposium on Mixed and Augmented Reality. IEEE, 2011: 127-136.

   • 代码：https://github.com/chrdiller/KinectFusionApp

4. ElasticFusion

   • 论文：Whelan T, Salas-Moreno R F, Glocker B, et al. [ElasticFusion: Real-time dense SLAM and light source estimation](https://spiral.imperial.ac.uk/bitstream/10044/1/39502/4/Whelan16ijrr.pdf)[J]. The International Journal of Robotics Research, 2016, 35(14): 1697-1716.

   • 代码：https://github.com/mp3guy/ElasticFusion

5. Kintinuous

   • ElasticFusion 同一个团队的工作，帝国理工 Stefan Leutenegger [谷歌学术](https://scholar.google.com/citations?user=SmGQ48gAAAAJ&hl=zh-CN&oi=sra)

   • 论文：Whelan T, Kaess M, Johannsson H, et al. [Real-time large-scale dense RGB-D SLAM with volumetric fusion](https://dspace.mit.edu/bitstream/handle/1721.1/97583/Leonard_Real-time.pdf%3Bjsessionid%3D8C351776D7D5E5C614AF641625837212?sequence%3D1)[J]. The International Journal of Robotics Research, 2015, 34(4-5): 598-626.

   • 代码：https://github.com/mp3guy/Kintinuous

6. ElasticReconstruction

   • 论文：Choi S, Zhou Q Y, Koltun V. [Robust reconstruction of indoor scenes](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Choi_Robust_Reconstruction_of_2015_CVPR_paper.pdf)[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015: 5556-5565.

   • 代码：https://github.com/qianyizh/ElasticReconstruction ；[作者主页](http://qianyi.info/publication.html)

7. FlashFusion

   • 论文：Han L, Fang L. [FlashFusion: Real-time Globally Consistent Dense 3D Reconstruction using CPU Computing](http://www.roboticsproceedings.org/rss14/p06.pdf)[C]. RSS, 2018.

   • **代码**（一直没放出来）：https://github.com/lhanaf/FlashFusion ； [Project Page](http://www.luvision.net/FlashFusion/?tdsourcetag=s_pctim_aiomsg)

8. RTAB-Map（激光视觉稠密重建）

   • 论文：Labbé M, Michaud F. [RTAB‐Map as an open‐source lidar and visual simultaneous localization and mapping library for large‐scale and long‐term online operation](https://pdfs.semanticscholar.org/3957/7f85f3b1a16f496a2160d1a71894d12c1acc.pdf)[J]. Journal of Field Robotics, 2019, 36(2): 416-446.

   • 代码：https://github.com/introlab/rtabmap ；[Video](https://www.youtube.com/user/matlabbe) ；[project page](http://introlab.github.io/rtabmap/)

9. RobustPCLReconstruction（户外稠密重建）

   • 论文：Lan Z, Yew Z J, Lee G H. [Robust Point Cloud Based Reconstruction of Large-Scale Outdoor Scenes](http://openaccess.thecvf.com/content_CVPR_2019/papers/Lan_Robust_Point_Cloud_Based_Reconstruction_of_Large-Scale_Outdoor_Scenes_CVPR_2019_paper.pdf)[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 9690-9698.

   • 代码：https://github.com/ziquan111/RobustPCLReconstruction ；[Video](https://www.youtube.com/watch?v=ZZQT_REkItU)

10. plane-opt-rgbd（室内平面重建）

• 论文：Wang C, Guo X. [Efficient Plane-Based Optimization of Geometry and Texture for Indoor RGB-D Reconstruction](http://openaccess.thecvf.com/content_CVPRW_2019/papers/SUMO/Wang_Efficient_Plane-Based_Optimization_of_Geometry_and_Texture_for_Indoor_RGB-D_CVPRW_2019_paper.pdf)[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2019: 49-53.

• 代码：https://github.com/chaowang15/plane-opt-rgbd

11. DenseSurfelMapping（稠密表面重建）

• 论文：Wang K, Gao F, Shen S. [Real-time scalable dense surfel mapping](https://arxiv.org/pdf/1909.04250.pdf)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 6919-6925.

• 代码：https://github.com/HKUST-Aerial-Robotics/DenseSurfelMapping

12. surfelmeshing（网格重建）

• 论文：Schöps T, Sattler T, Pollefeys M. [Surfelmeshing: Online surfel-based mesh reconstruction](https://arxiv.org/pdf/1810.00729.pdf)[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.

• 代码：https://github.com/puzzlepaint/surfelmeshing

13. DPPTAM（单目稠密重建）

• 论文：Concha Belenguer A, Civera Sancho J. [DPPTAM: Dense piecewise planar tracking and mapping from a monocular sequence](https://zaguan.unizar.es/record/36752/files/texto_completo.pdf)[C]//Proc. IEEE/RSJ Int. Conf. Intell. Rob. Syst. 2015 (ART-2015-92153).

• 代码：https://github.com/alejocb/dpptam

• 相关研究：基于超像素的单目 SLAM：[Using Superpixels in Monocular SLAM](http://webdiis.unizar.es/~jcivera/papers/concha_civera_icra14.pdf) ICRA 2014 ；[谷歌学术](https://scholar.google.com/citations?user=GIaG3CsAAAAJ&hl=zh-CN&oi=sra)

14. VI-MEAN（单目视惯稠密重建）

• 论文：Yang Z, Gao F, Shen S. [Real-time monocular dense mapping on aerial robots using visual-inertial fusion](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7989529)[C]//2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2017: 4552-4559.

• 代码：https://github.com/dvorak0/VI-MEAN ；[Video](https://www.youtube.com/watch?v=M4BMks6bQbc)

15. REMODE（单目概率稠密重建）

• 论文：Pizzoli M, Forster C, Scaramuzza D. [REMODE: Probabilistic, monocular dense reconstruction in real time](https://files.ifi.uzh.ch/rpg/website/rpg.ifi.uzh.ch/html/docs/ICRA14_Pizzoli.pdf)[C]//2014 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2014: 2609-2616.

• 原始开源代码：https://github.com/uzh-rpg/rpg_open_remode

• 与 ORB-SLAM2 结合版本：https://github.com/ayushgaud/ORB_SLAM2 https://github.com/ayushgaud/ORB_SLAM2

16. DeepFactors（实时的概率单目稠密 SLAM）

• 帝国理工学院戴森机器人实验室

• 论文：Czarnowski J, Laidlow T, Clark R, et al. [DeepFactors: Real-Time Probabilistic Dense Monocular SLAM](https://arxiv.org/pdf/2001.05049.pdf)[J]. arXiv preprint arXiv:2001.05049, 2020.

• 代码：https://github.com/jczarnowski/DeepFactors （还未放出）

• 其他论文：Bloesch M, Czarnowski J, Clark R, et al. [CodeSLAM—learning a compact, optimisable representation for dense visual SLAM](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bloesch_CodeSLAM_–_Learning_CVPR_2018_paper.pdf)[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 2560-2568.

17. probabilistic_mapping（单目概率稠密重建）

• 港科沈邵劼老师团队

• 论文：Ling Y, Wang K, Shen S. [Probabilistic dense reconstruction from a moving camera](https://arxiv.org/pdf/1903.10673.pdf)[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 6364-6371.

• 代码：https://github.com/ygling2008/probabilistic_mapping

• 另外一篇稠密重建文章的代码一直没放出来 [Github](https://github.com/ygling2008/dense_mapping) ：Ling Y, Shen S. [Real‐time dense mapping for online processing and navigation](https://onlinelibrary.wiley.com/doi/abs/10.1002/rob.21868)[J]. Journal of Field Robotics, 2019, 36(5): 1004-1036.

18. ORB-SLAM2 单目半稠密建图

• 论文：Mur-Artal R, Tardós J D. [Probabilistic Semi-Dense Mapping from Highly Accurate Feature-Based Monocular SLAM](https://www.researchgate.net/profile/Raul_Mur-Artal/publication/282807894_Probabilistic_Semi-Dense_Mapping_from_Highly_Accurate_Feature-Based_Monocular_SLAM/links/561cd04308ae6d17308ce267.pdf)[C]//Robotics: Science and Systems. 2015, 2015.

• **代码**（本身没有开源，贺博复现的一个版本）：https://github.com/HeYijia/ORB_SLAM2

• 加上线段之后的半稠密建图

  • 论文：He S, Qin X, Zhang Z, et al. [Incremental 3d line segment extraction from semi-dense slam](https://arxiv.org/pdf/1708.03275)[C]//2018 24th International Conference on Pattern Recognition (ICPR). IEEE, 2018: 1658-1663.

  • 代码：https://github.com/shidahe/semidense-lines

  • 作者在此基础上用于指导远程抓取操作的一项工作：https://github.com/atlas-jj/ORB-SLAM-free-space-carving

19. Voxgraph（SDF 体素建图）

• 论文：Reijgwart V, Millane A, Oleynikova H, et al. [Voxgraph: Globally Consistent, Volumetric Mapping Using Signed Distance Function Submaps](https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/385682/1/Voxgraph-ETHpreprintversion.pdf)[J]. IEEE Robotics and Automation Letters, 2019, 5(1): 227-234.

• 代码：https://github.com/ethz-asl/voxgraph

20. SegMap（三维分割建图）

• 论文：Dubé R, Cramariuc A, Dugas D, et al. [SegMap: 3d segment mapping using data-driven descriptors](https://arxiv.org/pdf/1804.09557)[J]. arXiv preprint arXiv:1804.09557, 2018.

• 代码：https://github.com/ethz-asl/segmap

21. OpenREALM：无人机实时建图框架

• 论文：Kern A, Bobbe M, Khedar Y, et al. [OpenREALM: Real-time Mapping for Unmanned Aerial Vehicles](https://arxiv.org/abs/2009.10492)[J]. arXiv preprint arXiv:2009.10492, 2020.

• 代码：https://github.com/laxnpander/OpenREALM

22. c-blox：可拓展的 TSDF 稠密建图

• 论文：Millane A, Taylor Z, Oleynikova H, et al. [C-blox: A scalable and consistent tsdf-based dense mapping approach](https://ieeexplore.ieee.org/abstract/document/8593427/)[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 995-1002.

• 代码：https://github.com/ethz-asl/cblox

2.优秀作者与实验室

1 美国卡耐基梅陇大学机器人研究所

Note

• 研究方向：机器人感知、结构，服务型、运输、制造业、现场机器

• 研究所主页：https://www.ri.cmu.edu/

• 下属 Field Robotic Center 主页：https://frc.ri.cmu.edu/

• 发表论文：https://www.ri.cmu.edu/pubs/

• Michael Kaess：个人主页 ，谷歌学术

• Sebastian Scherer：个人主页 ，谷歌学术

• Kaess M, Ranganathan A, Dellaert F. iSAM: Incremental smoothing and mapping[J]. IEEE Transactions on Robotics, 2008, 24(6): 1365-1378.

• Hsiao M, Westman E, Zhang G, et al. Keyframe-based dense planar SLAM[C]//2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2017: 5110-5117.

• Kaess M. Simultaneous localization and mapping with infinite planes[C]//2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2015: 4605-4611.

2 美国加州大学圣地亚哥分校语境机器人研究所

Note

• 研究方向：多模态环境理解，语义导航，自主信息获取

• 实验室主页：https://existentialrobotics.org/index.html

• 发表论文汇总：https://existentialrobotics.org/pages/publications.html

• Nikolay Atanasov：个人主页 谷歌学术

• 机器人状态估计与感知课程 ppt：https://natanaso.github.io/ece276a2019/schedule.html

• 语义 SLAM 经典论文：Bowman S L, Atanasov N, Daniilidis K, et al. Probabilistic data association for semantic slam[C]//2017 IEEE international conference on robotics and automation (ICRA). IEEE, 2017: 1722-1729.

• 实例网格模型定位与建图：Feng Q, Meng Y, Shan M, et al. Localization and Mapping using Instance-specific Mesh Models[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019: 4985-4991.

• 基于事件相机的 VIO：Zihao Zhu A, Atanasov N, Daniilidis K. Event-based visual inertial odometry[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017: 5391-5399.

3 美国特拉华大学机器人感知与导航组

Note

• 研究方向：SLAM、VINS、语义定位与建图等

• 实验室主页：https://sites.udel.edu/robot/

• 发表论文汇总：https://sites.udel.edu/robot/publications/

• Github 地址：https://github.com/rpng?page=2

• Geneva P, Eckenhoff K, Lee W, et al. Openvins: A research platform for visual-inertial estimation[C]//IROS 2019 Workshop on Visual-Inertial Navigation: Challenges and Applications, Macau, China. IROS 2019.（代码：https://github.com/rpng/open_vins ）

• Huai Z, Huang G. Robocentric visual-inertial odometry[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 6319-6326.（代码：https://github.com/rpng/R-VIO ）

• Zuo X, Geneva P, Yang Y, et al. Visual-Inertial Localization With Prior LiDAR Map Constraints[J]. IEEE Robotics and Automation Letters, 2019, 4(4): 3394-3401.

• Zuo X, Ye W, Yang Y, et al. Multimodal localization: Stereo over LiDAR map[J]. Journal of Field Robotics, 2020 （ 左星星博士谷歌学术）

• 黄国权教授主页

4 美国麻省理工学院航空航天实验室

Note

• 研究方向：位姿估计与导航，路径规划，控制与决策，机器学习与强化学习

• 实验室主页：http://acl.mit.edu/

• 发表论文：http://acl.mit.edu/publications （实验室的**学位论文**也可以在这里找到）

• 👦 Jonathan P. How 教授：[个人主页](http://www.mit.edu/people/jhow/) &emsp;[谷歌学术](https://scholar.google.com/citations?user=gX7rSCcAAAAJ&hl=en)

• 👦 **Kasra Khosoussi**（SLAM 图优化）：[谷歌学术](https://scholar.google.com/citations?user=SRCCuo0AAAAJ&hl=zh-CN&oi=sra)

• 📜 物体级 SLAM：Mu B, Liu S Y, Paull L, et al. [Slam with objects using a nonparametric pose graph](https://arxiv.org/pdf/1704.05959.pdf?source=post_page—————————)[C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016: 4602-4609.（代码：https://github.com/BeipengMu/objectSLAM）

• 📜 物体级 SLAM 导航：Ok K, Liu K, Frey K, et al. [Robust Object-based SLAM for High-speed Autonomous Navigation](http://groups.csail.mit.edu/rrg/papers/OkLiu19icra.pdf)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 669-675.

• 📜 SLAM 的图优化：Khosoussi, K., Giamou, M., Sukhatme, G., Huang, S., Dissanayake, G., and How, J. P., [Reliable Graphs for SLAM](https://journals.sagepub.com/doi/full/10.1177/0278364918823086) [C]//International Journal of Robotics Research (IJRR), 2019.

5 美国麻省理工学院 SPARK 实验室

Note

• 研究方向：移动机器人环境感知

• 实验室主页：http://web.mit.edu/sparklab/

• 👦 Luca Carlone 教授：[个人主页](https://lucacarlone.mit.edu/) &emsp;[谷歌学术](https://scholar.google.com/citations?user=U4kKRdMAAAAJ&hl=zh-CN&oi=sra)

• 📜 SLAM 经典综述：Cadena C, Carlone L, Carrillo H, et al. [Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age](https://arxiv.org/pdf/1606.05830)[J]. IEEE Transactions on robotics, 2016, 32(6): 1309-1332.

• 📜 VIO 流形预积分：Forster C, Carlone L, Dellaert F, et al. [On-Manifold Preintegration for Real-Time Visual–Inertial Odometry](https://arxiv.org/pdf/1512.02363)[J]. IEEE Transactions on Robotics, 2016, 33(1): 1-21.

• 📜 开源语义 SLAM：Rosinol A, Abate M, Chang Y, et al. [Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping](https://arxiv.org/pdf/1910.02490)[J]. arXiv preprint arXiv:1910.02490, 2019.（代码：https://github.com/MIT-SPARK/Kimera ）

6 美国麻省理工学院海洋机器人组

Note

• 研究方向：水下或陆地移动机器人导航与建图

• 实验室主页：https://marinerobotics.mit.edu/ （隶属于 MIT [计算机科学与人工智能实验室](https://www.csail.mit.edu/)）

• 👦 John Leonard 教授：[谷歌学术](https://scholar.google.com/citations?user=WPe7vWwAAAAJ&hl=zh-CN&authuser=1&oi=ao)

• 发表论文汇总：https://marinerobotics.mit.edu/biblio

• 📜 面向物体的 SLAM：Finman R, Paull L, Leonard J J. [Toward object-based place recognition in dense rgb-d maps](http://marinerobotics.mit.edu/sites/default/files/icra2015.pdf)[C]//ICRA Workshop Visual Place Recognition in Changing Environments, Seattle, WA. 2015.

• 📜 拓展 KinectFusion：Whelan T, Kaess M, Fallon M, et al. [Kintinuous: Spatially extended kinectfusion]()[J]. 2012.

• 📜 语义 SLAM 概率数据关联：Doherty K, Fourie D, Leonard J. [Multimodal semantic slam with probabilistic data association](https://marinerobotics.mit.edu/sites/default/files/doherty_icra2019_revised.pdf)[C]//2019 international conference on robotics and automation (ICRA). IEEE, 2019: 2419-2425.

7 美国明尼苏达大学多元自主机器人系统实验室

Note

• 研究方向：视觉、激光、惯性导航系统，移动设备大规模三维建模与定位

• 实验室主页：http://mars.cs.umn.edu/index.php

• 发表论文汇总：http://mars.cs.umn.edu/publications.php

• 👦 Stergios I. Roumeliotis：[个人主页](https://www-users.cs.umn.edu/~stergios/) ，[谷歌学术](https://scholar.google.com/citations?user=c5HeXxsAAAAJ&hl=zh-CN&oi=ao)

• 📜 移动设备 VIO：Wu K, Ahmed A, Georgiou G A, et al. [A Square Root Inverse Filter for Efficient Vision-aided Inertial Navigation on Mobile Devices](http://roboticsproceedings.org/rss11/p08.pdf)[C]//Robotics: Science and Systems. 2015, 2.（项目主页：http://mars.cs.umn.edu/research/sriswf.php ）

• 📜 移动设备大规模三维半稠密建图：Guo C X, Sartipi K, DuToit R C, et al. [Resource-aware large-scale cooperative three-dimensional mapping using multiple mobile devices](https://pdfs.semanticscholar.org/e0fd/6d963307a0d5d6dfb6f05ad21845dd4f40c8.pdf)[J]. IEEE Transactions on Robotics, 2018, 34(5): 1349-1369. （项目主页：http://mars.cs.umn.edu/research/semi_dense_mapping.php ）

• 📜 VIO 相关研究：http://mars.cs.umn.edu/research/vins_overview.php

8 美国宾夕法尼亚大学 Vijay Kumar 实验室

Note

• 研究方向：自主微型无人机

• 实验室主页：https://www.kumarrobotics.org/

• 发表论文：https://www.kumarrobotics.org/publications/

• 研究成果视频：https://www.youtube.com/user/KumarLabPenn/videos

• 📜 无人机半稠密 VIO：Liu W, Loianno G, Mohta K, et al. [Semi-Dense Visual-Inertial Odometry and Mapping for Quadrotors with SWAP Constraints](https://www.cis.upenn.edu/~kostas/mypub.dir/wenxin18icra.pdf)[C]//2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018: 1-6.

• 📜 语义数据关联：Liu X, Chen S W, Liu C, et al. [Monocular Camera Based Fruit Counting and Mapping with Semantic Data Association](https://arxiv.org/pdf/1811.01417)[J]. IEEE Robotics and Automation Letters, 2019, 4(3): 2296-2303.

9 Srikumar Ramalingam（美国犹他大学计算机学院）

Note

• 研究方向：三维重构、语义分割、视觉 SLAM、图像定位、深度神经网络

• 👦 Srikumar Ramalingam：[个人主页](https://www.cs.utah.edu/~srikumar/) &emsp; [谷歌学术](https://scholar.google.com/citations?user=6m1ptOgAAAAJ&hl=en/)

• 📜 点面 SLAM：Taguchi Y, Jian Y D, Ramalingam S, et al. [Point-plane SLAM for hand-held 3D sensors](https://merl.com/publications/docs/TR2013-031.pdf)[C]//2013 IEEE international conference on robotics and automation. IEEE, 2013: 5182-5189.

• 📜 点线定位：Ramalingam S, Bouaziz S, Sturm P. [Pose estimation using both points and lines for geo-localization](https://hal.inria.fr/inria-00590279/document)[C]//2011 IEEE International Conference on Robotics and Automation. IEEE, 2011: 4716-4723.（[视频](https://www.youtube.com/watch?v=wc7hK0zEkCw&feature=emb_logo)）

• 📜 2D 3D 定位：Ataer-Cansizoglu E, Taguchi Y, Ramalingam S. [Pinpoint SLAM: A hybrid of 2D and 3D simultaneous localization and mapping for RGB-D sensors](http://yuichitaguchi.com/pub/16ICRA_PinpointSLAM.pdf)[C]//2016 IEEE international conference on robotics and automation (ICRA). IEEE, 2016: 1300-1307.（[视频](https://www.youtube.com/watch?v=iZ1psxcMvrQ&feature=emb_logo)）

10 Frank Dellaert（美国佐治亚理工学院机器人与智能机器研究中心）

Note

• 研究方向：SLAM，图像时空重构

• 👦 [个人主页](https://www.cc.gatech.edu/~dellaert/FrankDellaert/Frank_Dellaert/Frank_Dellaert.html)，[谷歌学术](https://scholar.google.com/citations?user=ZxXBaswAAAAJ&hl=en)

• 📜 因子图：Dellaert F. [Factor graphs and GTSAM: A hands-on introduction](https://smartech.gatech.edu/handle/1853/45226)[R]. Georgia Institute of Technology, 2012. （GTSAM 代码：http://borg.cc.gatech.edu/ ）

• 📜 多机器人分布式 SLAM：Cunningham A, Wurm K M, Burgard W, et al. [Fully distributed scalable smoothing and mapping with robust multi-robot data association](https://smartech.gatech.edu/bitstream/handle/1853/44686/Cunningham12icra.pdf?sequence=1&isAllowed=y)[C]//2012 IEEE International Conference on Robotics and Automation. IEEE, 2012: 1093-1100.

• 📜 Choudhary S, Trevor A J B, Christensen H I, et al. [SLAM with object discovery, modeling and mapping](https://smartech.gatech.edu/bitstream/handle/1853/53723/Choudhary14iros.pdf)[C]//2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2014: 1018-1025.

11 Patricio Vela （美国佐治亚理工学院智能视觉与自动化实验室

Note

• 研究方向：机器人控制、定位与导航

• 实验室主页：http://ivalab.gatech.edu/

• 👦 Patricio Vela [个人主页](https://pvela.gatech.edu/)

• 👦 赵轶璞 [个人主页](https://sites.google.com/site/zhaoyipu/home?authuser=0) &emsp; [谷歌学术](https://scholar.google.com/citations?user=HiM_WcYAAAAJ&hl=zh-CN&authuser=1&oi=ao)

• 📜 Zhao Y, Smith J S, Karumanchi S H, et al. [Closed-Loop Benchmarking of Stereo Visual-Inertial SLAM Systems: Understanding the Impact of Drift and Latency on Tracking Accuracy](https://arxiv.org/pdf/2003.01317)[J]. arXiv preprint arXiv:2003.01317, 2020.

• 📜 Zhao Y, Vela P A. [Good feature selection for least squares pose optimization in VO/VSLAM](https://arxiv.org/pdf/1905.07807)[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 1183-1189.（代码：https://github.com/ivalab/FullResults_GoodFeature ）

• 📜 Zhao Y, Vela P A. [Good line cutting: Towards accurate pose tracking of line-assisted VO/VSLAM](http://openaccess.thecvf.com/content_ECCV_2018/papers/Yipu_Zhao_Good_Line_Cutting_ECCV_2018_paper.pdf)[C]//Proceedings of the European Conference on Computer Vision (ECCV). 2018: 516-531. （代码：https://github.com/ivalab/GF_PL_SLAM ）

12 加拿大蒙特利尔大学 机器人与嵌入式 AI 实验室

Note

• 研究方向：SLAM，不确定性建模

• 实验室主页：http://montrealrobotics.ca/

• 👦 Liam Paull 教授：[个人主页](https://liampaull.ca/index.html)&emsp;[谷歌学术](https://scholar.google.com/citations?user=H9xADK0AAAAJ&hl=zh-CN&oi=ao)

• 📜 Mu B, Liu S Y, Paull L, et al. [Slam with objects using a nonparametric pose graph](https://arxiv.org/pdf/1704.05959.pdf?source=post_page—————————)[C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016: 4602-4609.（代码：https://github.com/BeipengMu/objectSLAM）

• 📜 Murthy Jatavallabhula K, Iyer G, Paull L. [gradSLAM: Dense SLAM meets Automatic Differentiation](http://adsabs.harvard.edu/abs/2019arXiv191010672M)[J]. arXiv preprint arXiv:1910.10672, 2019.（代码：https://github.com/montrealrobotics/gradSLAM ）

13. 加拿大舍布鲁克大学智能、交互、综合、跨学科机器人实验室

Note

• 研究方向：移动机器人软硬件设计

• 实验室主页：https://introlab.3it.usherbrooke.ca/

• 📜 激光视觉稠密重建：Labbé M, Michaud F. [RTAB‐Map as an open‐source lidar and visual simultaneous localization and mapping library for large‐scale and long‐term online operation](https://pdfs.semanticscholar.org/3957/7f85f3b1a16f496a2160d1a71894d12c1acc.pdf)[J]. Journal of Field Robotics, 2019, 36(2): 416-446.

• 代码：https://github.com/introlab/rtabmap

• 项目主页：http://introlab.github.io/rtabmap/

14. 瑞士苏黎世大学机器人与感知课题组

Note

• 研究方向：移动机器人、无人机环境感知与导航，VISLAM，事件相机

• 实验室主页：http://rpg.ifi.uzh.ch/index.html

• 发表论文汇总：http://rpg.ifi.uzh.ch/publications.html

• Github 代码公开地址：https://github.com/uzh-rpg

• 📜 Forster C, Pizzoli M, Scaramuzza D. [SVO: Fast semi-direct monocular visual odometry](https://www.zora.uzh.ch/id/eprint/125453/1/ICRA14_Forster.pdf)[C]//2014 IEEE international conference on robotics and automation (ICRA). IEEE, 2014: 15-22.

• 📜 VO/VIO 轨迹评估工具 rpg_trajectory_evaluation：https://github.com/uzh-rpg/rpg_trajectory_evaluation

• 📜 事件相机项目主页：http://rpg.ifi.uzh.ch/research_dvs.html

• 👦 人物：[Davide Scaramuzza](http://rpg.ifi.uzh.ch/people_scaramuzza.html) &emsp;[张子潮](https://www.ifi.uzh.ch/en/rpg/people/zichao.html)

15. 瑞士苏黎世联邦理工计算机视觉与几何实验室

Note

• 研究方向：定位、三维重建、语义分割、机器人视觉

• 实验室主页：http://www.cvg.ethz.ch/index.php

• 发表论文：http://www.cvg.ethz.ch/publications/

• 📜 视觉语义里程计：Lianos K N, Schonberger J L, Pollefeys M, et al. [Vso: Visual semantic odometry](http://openaccess.thecvf.com/content_ECCV_2018/papers/Konstantinos-Nektarios_Lianos_VSO_Visual_Semantic_ECCV_2018_paper.pdf)[C]//Proceedings of the European conference on computer vision (ECCV). 2018: 234-250.

• 📜 视觉语义定位：CVPR 2018 [Semantic visual localization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Schonberger_Semantic_Visual_Localization_CVPR_2018_paper.pdf)

• 作者博士学位论文：2018 [Robust Methods for Accurate and Efficient 3D Modeling from Unstructured Imagery](https://www.research-collection.ethz.ch/handle/20.500.11850/295763)

• 📜 大规模户外建图：Bârsan I A, Liu P, Pollefeys M, et al. [Robust dense mapping for large-scale dynamic environments](https://arxiv.org/pdf/1905.02781.pdf?utm_term)[C]//2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018: 7510-7517.

• 代码：https://github.com/AndreiBarsan/DynSLAM

• 作者博士学位论文：Barsan I A. [Simultaneous localization and mapping in dynamic scenes](https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/202829/1/Barsan_Ioan.pdf)[D]. ETH Zurich, Department of Computer Science, 2017.

• 👦 Marc Pollefeys：[个人主页](http://people.inf.ethz.ch/pomarc/index.html)，[谷歌学术](https://scholar.google.com/citations?user=YYH0BjEAAAAJ&hl=zh-CN&oi=ao)

• 👦 Johannes L. Schönberger：[个人主页](https://demuc.de/)，[谷歌学术](https://scholar.google.com/citations?user=MlcMCd0AAAAJ)

16. 英国帝国理工学院戴森机器人实验室

Note

• 研究方向：机器人视觉场景与物体理解、机器人操纵

• 实验室主页：https://www.imperial.ac.uk/dyson-robotics-lab/

• 发表论文：https://www.imperial.ac.uk/dyson-robotics-lab/publications/

• 代表性工作：MonoSLAM、CodeSLAM、ElasticFusion、KinectFusion

• 📜 ElasticFusion：Whelan T, Leutenegger S, Salas-Moreno R, et al. [ElasticFusion: Dense SLAM without a pose graph](https://spiral.imperial.ac.uk/bitstream/10044/1/23438/2/whelan2015rss.pdf)[C]. Robotics: Science and Systems, 2015.（代码：https://github.com/mp3guy/ElasticFusion ）

• 📜 Semanticfusion：McCormac J, Handa A, Davison A, et al. [Semanticfusion: Dense 3d semantic mapping with convolutional neural networks](https://arxiv.org/pdf/1609.05130)[C]//2017 IEEE International Conference on Robotics and automation (ICRA). IEEE, 2017: 4628-4635.（代码：https://github.com/seaun163/semanticfusion ）

• 📜 Code-SLAM：Bloesch M, Czarnowski J, Clark R, et al. [CodeSLAM—learning a compact, optimisable representation for dense visual SLAM](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bloesch_CodeSLAM_–_Learning_CVPR_2018_paper.pdf)[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 2560-2568.

• 👦 Andrew Davison：[谷歌学术](https://scholar.google.com/citations?user=A0ae1agAAAAJ&hl=zh-CN&oi=ao)

17. 英国牛津大学信息工程学

Note

• 研究方向：SLAM、目标跟踪、运动结构、场景增强、移动机器人运动规划、导航与建图等等等

• 实验室主页：http://www.robots.ox.ac.uk/

• 主动视觉实验室：http://www.robots.ox.ac.uk/ActiveVision/

• 牛津机器人学院：https://ori.ox.ac.uk/

• 发表论文汇总：

• 主动视觉实验室：http://www.robots.ox.ac.uk/ActiveVision/Publications/index.html

• 机器人学院：https://ori.ox.ac.uk/publications/papers/

• 代表性工作：

• 📜 Klein G, Murray D. [PTAM: Parallel tracking and mapping for small AR workspaces](https://dl.acm.org/ft_gateway.cfm?id=1514363&type=pdf)[C]//2007 6th IEEE and ACM international symposium on mixed and augmented reality. IEEE, 2007: 225-234.

• 📜 RobotCar 数据集：https://robotcar-dataset.robots.ox.ac.uk/

• 👦 **人物**（谷歌学术）：[David Murray](https://scholar.google.com.hk/citations?hl=zh-CN&user=O5QreiwAAAAJ) &emsp; [Maurice Fallon](https://ori.ox.ac.uk/ori-people/maurice-fallon/)

• 部分博士学位论文可以在这里搜到：https://ora.ox.ac.uk/

18. 德国慕尼黑工业大学计算机视觉组

Note

• 研究方向：三维重建、机器人视觉、深度学习、视觉 SLAM 等

• 实验室主页：https://vision.in.tum.de/research/vslam

• 发表论文汇总：https://vision.in.tum.de/publications

• 代表作：DSO、LDSO、LSD_SLAM、DVO_SLAM

• 📜 DSO：Engel J, Koltun V, Cremers D. [Direct sparse odometry](https://ieeexplore.ieee.org/iel7/34/4359286/07898369.pdf)[J]. IEEE transactions on pattern analysis and machine intelligence, 2017, 40(3): 611-625.（代码：https://github.com/JakobEngel/dso ）

• 📜 LSD-SLAM： Engel J, Schöps T, Cremers D. [LSD-SLAM: Large-scale direct monocular SLAM](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.646.7193&rep=rep1&type=pdf)[C]//European conference on computer vision. Springer, Cham, 2014: 834-849.（代码：https://github.com/tum-vision/lsd_slam ）2.

• Github 地址：https://github.com/tum-vision

• 👦 Daniel Cremers 教授：[个人主页](https://vision.in.tum.de/members/cremers) [谷歌学术](https://scholar.google.com/citations?user=cXQciMEAAAAJ)

• 👦 **Jakob Engel**（LSD-SLAM，DSO 作者）：[个人主页](https://jakobengel.github.io/) &emsp;[谷歌学术](https://scholar.google.de/citations?user=ndOMZXMAAAAJ)

19. 德国马克斯普朗克智能系统研究所嵌入式视觉组

Note

• 研究方向：智能体自主环境理解、导航与物体操纵

• 实验室主页：https://ev.is.tuebingen.mpg.de/

• 👦 负责人 **Jörg Stückler**（前 TUM 教授）：[个人主页](https://ev.is.tuebingen.mpg.de/person/jstueckler) &emsp; [谷歌学术](https://scholar.google.de/citations?user=xrOzfucAAAAJ&hl=de)

• 📜 发表论文汇总：https://ev.is.tuebingen.mpg.de/publications

• Kasyanov A, Engelmann F, Stückler J, et al. [Keyframe-based visual-inertial online SLAM with relocalization](https://arxiv.org/pdf/1702.02175)[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017: 6662-6669.

• 📜 Strecke M, Stuckler J. [EM-Fusion: Dynamic Object-Level SLAM with Probabilistic Data Association](http://openaccess.thecvf.com/content_ICCV_2019/papers/Strecke_EM-Fusion_Dynamic_Object-Level_SLAM_With_Probabilistic_Data_Association_ICCV_2019_paper.pdf)[C]//Proceedings of the IEEE International Conference on Computer Vision. 2019: 5865-5874.

• 📜 Usenko, V., Demmel, N., Schubert, D., Stückler, J., Cremers, D. [Visual-Inertial Mapping with Non-Linear Factor Recovery](https://arxiv.org/pdf/1904.06504) IEEE Robotics and Automation Letters (RA-L), 5, 2020

20. 德国弗莱堡大学智能自主系统实验室

Note

• 研究方向：多机器人导航与协作，环境建模与状态估计

• 实验室主页：http://ais.informatik.uni-freiburg.de/index_en.php

• 发表论文汇总：http://ais.informatik.uni-freiburg.de/publications/index_en.php （学位论文也可以在这里找到）

• 👦 Wolfram Burgard：[谷歌学术](https://scholar.google.com/citations?user=zj6FavAAAAAJ&hl=zh-CN&oi=ao)

• 开放数据集：http://aisdatasets.informatik.uni-freiburg.de/

• 📜 RGB-D SLAM：Endres F, Hess J, Sturm J, et al. [3-D mapping with an RGB-D camera](http://perpustakaan.unitomo.ac.id/repository/3-D%20Mapping%20With%20an%20RGB-D%20Camera06594910.pdf)[J]. IEEE transactions on robotics, 2013, 30(1): 177-187.（代码：https://github.com/felixendres/rgbdslam_v2 ）

• 📜 跨季节的 SLAM：Naseer T, Ruhnke M, Stachniss C, et al. [Robust visual SLAM across seasons](http://ais.informatik.uni-freiburg.de/publications/papers/naseer15iros.pdf)[C]//2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2015: 2529-2535.

• 📜 博士学位论文：[Robust Graph-Based Localization and Mapping](http://ais.informatik.uni-freiburg.de/publications/papers/agarwal15phd.pdf) 2015

• 📜 博士学位论文：[Discovering and Leveraging Deep Multimodal Structure for Reliable Robot Perception and Localization](http://ais.informatik.uni-freiburg.de/publications/papers/valada19phd.pdf) 2019

• 📜 博士学位论文：[Robot Localization and Mapping in Dynamic Environments](https://freidok.uni-freiburg.de/fedora/objects/freidok:149938/datastreams/FILE1/content) 2019

21. 西班牙萨拉戈萨大学机器人、感知与实时组 SLAM 实验室

Note

• 研究方向：视觉 SLAM、物体 SLAM、非刚性 SLAM、机器人、增强现实

• 实验室主页：http://robots.unizar.es/slamlab/

• 发表论文：http://robots.unizar.es/slamlab/?extra=3 （论文好像没更新，可以访问下面实验室大佬的谷歌学术查看最新论文）

• 👦 J. M. M. Montiel：[谷歌学术](https://scholar.google.com/citations?user=D99JRxwAAAAJ&hl=zh-CN&oi=sra)

• 📜 Mur-Artal R, Tardós J D. [Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras](https://github.com/raulmur/ORB_SLAM2)[J]. IEEE Transactions on Robotics, 2017, 33(5): 1255-1262.

• Gálvez-López D, Salas M, Tardós J D, et al. [Real-time monocular object slam](https://arxiv.org/pdf/1504.02398.pdf)[J]. Robotics and Autonomous Systems, 2016, 75: 435-449.

• 📜 Strasdat H, Montiel J M M, Davison A J. [Real-time monocular SLAM: Why filter?](http://www.hauke.strasdat.net/files/strasdat2010icra.pdf)[C]//2010 IEEE International Conference on Robotics and Automation. IEEE, 2010: 2657-2664.

• 📜 Zubizarreta J, Aguinaga I, Montiel J M M. [Direct sparse mapping](https://arxiv.org/pdf/1904.06577)[J]. arXiv preprint arXiv:1904.06577, 2019.

• Elvira R, Tardós J D, Montiel J M M. [ORBSLAM-Atlas: a robust and accurate multi-map system](https://arxiv.org/pdf/1908.11585)[J]. arXiv preprint arXiv:1908.11585, 2019.

22. 西班牙马拉加大学机器感知与智能机器人课题组

Note

• 研究方向：自主机器人、人工嗅觉、计算机视觉

• 实验室主页：http://mapir.uma.es/mapirwebsite/index.php/topics-2.html

• 发表论文汇总：http://mapir.isa.uma.es/mapirwebsite/index.php/publications-menu-home.html

• 📜 Gomez-Ojeda R, Moreno F A, Zuñiga-Noël D, et al. [PL-SLAM: a stereo SLAM system through the combination of points and line segments](https://arxiv.org/pdf/1705.09479)[J]. IEEE Transactions on Robotics, 2019, 35(3): 734-746.（代码：https://github.com/rubengooj/pl-slam ）

• 👦 [Francisco-Angel Moreno](http://mapir.isa.uma.es/mapirwebsite/index.php/people/199-francisco-moreno-due%C3%B1as)

• 👦 [Ruben Gomez-Ojeda](https://scholar.google.com/citations?user=7jne0V4AAAAJ&hl=zh-CN&oi=sra) 点线 SLAM

• 📜 Gomez-Ojeda R, Briales J, Gonzalez-Jimenez J. [PL-SVO: Semi-direct Monocular Visual Odometry by combining points and line segments](http://mapir.isa.uma.es/rgomez/publications/iros16plsvo.pdf)[C]//Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on. IEEE, 2016: 4211-4216.（代码：https://github.com/rubengooj/pl-svo ）

• 📜 Gomez-Ojeda R, Gonzalez-Jimenez J. [Robust stereo visual odometry through a probabilistic combination of points and line segments](https://riuma.uma.es/xmlui/bitstream/handle/10630/11515/icra16rgo.pdf?sequence=1&isAllowed=y)[C]//2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2016: 2521-2526.（代码：https://github.com/rubengooj/stvo-pl ）

• 📜 Gomez-Ojeda R, Zuñiga-Noël D, Moreno F A, et al. [PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments](https://arxiv.org/pdf/1705.09479.pdf)[J]. arXiv preprint arXiv:1705.09479, 2017.（代码：https://github.com/rubengooj/pl-slam ）

23. Alejo Concha（Oculus VR，西班牙萨拉戈萨大学）

Note

• 研究方向：SLAM，单目稠密重建，传感器融合

• 👦 个人主页：https://sites.google.com/view/alejoconcha/ &emsp; [谷歌学术](https://scholar.google.com/citations?user=GIaG3CsAAAAJ&hl=zh-CN&oi=sra)

• Github：https://github.com/alejocb

• 📜 IROS 2015 单目平面重建：[DPPTAM: Dense piecewise planar tracking and mapping from a monocular sequence](https://zaguan.unizar.es/record/36752/files/texto_completo.pdf) （代码：https://github.com/alejocb/dpptam ）

• 📜 IROS 2017 开源 RGB-D SLAM：[RGBDTAM: A Cost-Effective and Accurate RGB-D Tracking and Mapping System](http://webdiis.unizar.es/~jcivera/papers/concha_etal_icra16.pdf)（代码：https://github.com/alejocb/rgbdtam ）

• 📜 ICRA 2016：[Visual-inertial direct SLAM](http://webdiis.unizar.es/~jcivera/papers/concha_etal_icra16.pdf)

• 📜 ICRA 2014：[Using Superpixels in Monocular SLAM](https://www.researchgate.net/profile/Alejo_Concha/publication/281559193_Using_superpixels_in_monocular_SLAM/links/55edffcb08aedecb68fc6ac2/Using-superpixels-in-monocular-SLAM.pdf)

• RSS 2014：[Manhattan and Piecewise-Planar Constraints for Dense Monocular Mapping](http://roboticsproceedings.org/rss10/p16.pdf)

24. 奥地利格拉茨技术大学计算机图形学与视觉研究所

Note

• 研究方向：AR/VR，机器人视觉，机器学习，目标识别与三维重建

• 实验室主页：https://www.tugraz.at/institutes/icg/home/

• 👦 Friedrich Fraundorfer 教授：[团队主页](https://www.tugraz.at/institutes/icg/research/team-fraundorfer/) &emsp;[谷歌学术](https://scholar.google.com/citations?user=M0boL5kAAAAJ&hl=zh-CN&oi=sra)

• 📜 [Visual Odometry: Part I The First 30 Years and Fundamentals](http://www.eng.auburn.edu/~troppel/courses/7970%202015A%20AdvMobRob%20sp15/literature/vis%20odom%20tutor%20part1%20.pdf)

• 📜 [Visual Odometry: Part II: Matching, Robustness, Optimization, and Applications](https://www.zora.uzh.ch/id/eprint/71030/1/Fraundorfer_Scaramuzza_Visual_odometry.pdf)

• 📜 Schenk F, Fraundorfer F. [RESLAM: A real-time robust edge-based SLAM system](https://ieeexplore.ieee.org/abstract/document/8794462/)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 154-160.（代码：https://github.com/fabianschenk/RESLAM ）

• 👦 Dieter Schmalstieg 教授：[团队主页](https://www.tugraz.at/institutes/icg/research/team-schmalstieg/) &emsp;[谷歌学术](https://scholar.google.com/citations?user=xXu8K6IAAAAJ&hl=zh-CN&oi=ao)

• 📜 教科书：[Augmented Reality: Principles and Practice](augmentedrealitybook.org)

• 📜 Arth C, Pirchheim C, Ventura J, et al. [Instant outdoor localization and slam initialization from 2.5 d maps](https://ieeexplore.ieee.org/abstract/document/7164332/)[J]. IEEE transactions on visualization and computer graphics, 2015, 21(11): 1309-1318.

• 📜 Hachiuma R, Pirchheim C, Schmalstieg D, et al. [DetectFusion: Detecting and Segmenting Both Known and Unknown Dynamic Objects in Real-time SLAM](https://arxiv.org/pdf/1907.09127)[J]. arXiv preprint arXiv:1907.09127, 2019.

25. 波兰波兹南工业大学移动机器人实验室

Note

• 研究方向：SLAM，机器人运动规划，控制

• 实验室主页：http://lrm.put.poznan.pl/

• Github 主页：https://github.com/LRMPUT

• 📜 Wietrzykowski J. [On the representation of planes for efficient graph-based slam with high-level features](https://yadda.icm.edu.pl/baztech/element/bwmeta1.element.baztech-7ac7a8f3-9caa-4a34-8a27-8f6c5f43408b)[J]. Journal of Automation Mobile Robotics and Intelligent Systems, 2016, 10.（代码：https://github.com/LRMPUT/PlaneSLAM ）

• 📜 Wietrzykowski J, Skrzypczyński P. [PlaneLoc: Probabilistic global localization in 3-D using local planar features](https://www.sciencedirect.com/science/article/pii/S0921889018303701)[J]. Robotics and Autonomous Systems, 2019.（代码：https://github.com/LRMPUT/PlaneLoc ）

• 📜 PUTSLAM：http://lrm.put.poznan.pl/putslam/

26. Alexander Vakhitov（三星莫斯科 AI 中心）

Note

• 研究方向：SLAM，几何视觉

• 👦 个人主页：https://alexandervakhitov.github.io/ ，[谷歌学术](https://scholar.google.ru/citations?user=g_2iut0AAAAJ&hl=ru%22)

• 📜 点线 SLAM：ICRA 2017 [PL-SLAM: Real-time monocular visual SLAM with points and lines](https://upcommons.upc.edu/bitstream/handle/2117/110259/1836-PL-SLAM–Real-Time-Monocular-Visual-SLAM-with-Points-and-Lines.pdf)

• 📜 点线定位：Pumarola A, Vakhitov A, Agudo A, et al. [Relative localization for aerial manipulation with PL-SLAM](https://upcommons.upc.edu/bitstream/handle/2117/182388/2205-Relative-localization-for-aerial-manipulation-with-PL-SLAM.pdf)[M]//Aerial Robotic Manipulation. Springer, Cham, 2019: 239-248.

• 📜 学习型线段：IEEE Access 2019 [Learnable line segment descriptor for visual SLAM](https://ieeexplore.ieee.org/iel7/6287639/6514899/08651490.pdf)（代码：https://github.com/alexandervakhitov/lld-slam ）

27. 澳大利亚昆士兰科技大学机器人技术中心

Note

• 研究方向：脑启发式机器人，采矿机器人，机器人视觉

• 实验室主页：https://www.qut.edu.au/research/centre-for-robotics

• 开源代码：https://research.qut.edu.au/qcr/open-source-code/

• 👦 Niko Sünderhauf：[个人主页](https://nikosuenderhauf.github.io/) ，[谷歌学术](https://scholar.google.com/citations?user=WnKjfFEAAAAJ&hl=zh-CN&oi=ao)

• 📜 RA-L 2018 二次曲面 SLAM：[QuadricSLAM: Dual quadrics from object detections as landmarks in object-oriented SLAM](https://ieeexplore.ieee.org/abstract/document/8440105/)

• 📜 Nicholson L, Milford M, Sunderhauf N. [QuadricSLAM: Dual quadrics as SLAM landmarks](http://openaccess.thecvf.com/content_cvpr_2018_workshops/papers/w9/Nicholson_QuadricSLAM_Dual_Quadrics_CVPR_2018_paper.pdf)[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2018: 313-314.

• 📜 Semantic SLAM 项目主页：http://www.semanticslam.ai/

• 📜 IROS 2017：[Meaningful maps with object-oriented semantic mapping](https://arxiv.org/pdf/1609.07849)

• 👦 Michael Milford：谷歌学术 https://scholar.google.com/citations?user=TDSmCKgAAAAJ&hl=zh-CN&oi=ao

• 📜 ICRA 2012：[SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights](http://www.cim.mcgill.ca/~dudek/417/Resources/seqslam-milford.pdf) （代码：https://michaelmilford.com/seqslam/）

• 📜 Ball D, Heath S, Wiles J, et al. [OpenRatSLAM: an open source brain-based SLAM system](https://static.springer.com/sgw/documents/1388513/application/pdf/10-3.pdf)[J]. Autonomous Robots, 2013, 34(3): 149-176.（代码：https://openslam-org.github.io/openratslam.html ）

• 📜 Yu F, Shang J, Hu Y, et al. [NeuroSLAM: a brain-inspired SLAM system for 3D environments](https://link.springer.com/article/10.1007/s00422-019-00806-9)[J]. Biological Cybernetics, 2019, 113(5-6): 515-545. （代码：https://github.com/cognav/NeuroSLAM ）

28. 澳大利亚机器人视觉中心

Note

• 研究方向：机器人感知、理解与学习 （集合了昆士兰科技大学，澳大利亚国立大学，阿德莱德大学，昆士兰大学等学校机器人领域的研究者）

• 实验室主页：https://www.roboticvision.org/

• 人物：https://www.roboticvision.org/rv_person_category/researchers/

• 发表论文汇总：https://www.roboticvision.org/publications/scientific-publications/

• 👦 Yasir Latif：[个人主页](http://ylatif.github.io/)，[谷歌学术](https://scholar.google.com/citations?user=pGsO6EkAAAAJ&hl=zh-CN)

• 📜 Latif Y, Cadena C, Neira J. [Robust loop closing over time for pose graph SLAM](http://webdiis.unizar.es/~ylatif/papers/IJRR.pdf)[J]. The International Journal of Robotics Research, 2013, 32(14): 1611-1626.

• 📜 Latif Y, Cadena C, Neira J. [Robust loop closing over time](https://pdfs.semanticscholar.org/62fb/619f7fc036c4dfb4c55a7c53907a112fe001.pdf)[C]//Proc. Robotics: Science Systems. 2013: 233-240.（代码：https://github.com/ylatif/rrr ）

• 👦 Ian D Reid：谷歌学术：https://scholar.google.com/citations?user=ATkNLcQAAAAJ&hl=zh-CN&oi=sra

• 📜 ICRA 2019：[Real-time monocular object-model aware sparse SLAM](https://arxiv.org/pdf/1809.09149)

• 📜 Reid I. [Towards semantic visual SLAM](https://ieeexplore.ieee.org/abstract/document/7064267/)[C]//2014 13th International Conference on Control Automation Robotics & Vision (ICARCV). IEEE, 2014: 1-1.

29. 日本国立先进工业科学技术研究所

Note

• 人工智能研究中心：https://www.airc.aist.go.jp/en/intro/

• 👦 Ken Sakurada：[个人主页](https://kensakurada.github.io/)，[谷歌学术](https://scholar.google.com/citations?user=Q4JO-ncAAAAJ&hl=zh-CN&oi=sra)

• 📜 Sumikura S, Shibuya M, Sakurada K. [OpenVSLAM: A Versatile Visual SLAM Framework](https://dl.acm.org/doi/pdf/10.1145/3343031.3350539)[C]//Proceedings of the 27th ACM International Conference on Multimedia. 2019: 2292-2295.（代码：https://github.com/xdspacelab/openvslam ）

• 👦 Shuji Oishi：[谷歌学术](https://scholar.google.com/citations?user=wlPYSDgAAAAJ&hl=zh-CN&oi=sra)

• 📜 极稠密特征点建图：Yokozuka M, Oishi S, Thompson S, et al. [VITAMIN-E: visual tracking and MappINg with extremely dense feature points](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yokozuka_VITAMIN-E_VIsual_Tracking_and_MappINg_With_Extremely_Dense_Feature_Points_CVPR_2019_paper.pdf)[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2019: 9641-9650.

• 📜 Oishi S, Inoue Y, Miura J, et al. [SeqSLAM++: View-based robot localization and navigation](https://staff.aist.go.jp/shuji.oishi/assets/papers/published/SeqSLAM++_RAS2019.pdf)[J]. Robotics and Autonomous Systems, 2019, 112: 13-21.

30. Pyojin Kim（韩国首尔大学自主机器人实验室）

Note

• 研究方向：视觉里程计，定位，AR/VR

• 👦 [个人主页](http://pyojinkim.com/)，[谷歌学术](https://scholar.google.com/citations?user=NHpe_8IAAAAJ&hl=en)

• 📜 平面 SLAM：ECCV 2018：[Linear RGB-D SLAM for planar environments](http://openaccess.thecvf.com/content_ECCV_2018/papers/Pyojin_Kim_Linear_RGB-D_SLAM_ECCV_2018_paper.pdf)

• 📜 光照变化下的鲁棒 SLAM：ICRA 2017：[Robust visual localization in changing lighting conditions](https://www.nasa.gov/sites/default/files/atoms/files/kim2017robust.pdf)

• 📜 线面 SLAM：CVPR 2018：[Indoor RGB-D Compass from a Single Line and Plane](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kim_Indoor_RGB-D_Compass_CVPR_2018_paper.pdf)

• 📜 博士学位论文：[Low-Drift Visual Odometry for Indoor Robotics](http://pyojinkim.com/download/papers/2019_pjinkim_PhDthesis_low.pdf)

31. 香港科技大学空中机器人实验室

Note

• 研究方向：空中机器人在复杂环境下的自主运行，包括状态估计、建图、运动规划、多机器人协同以及低成本传感器和计算组件的实验平台开发。

• 实验室主页：http://uav.ust.hk/

• 发表论文：http://uav.ust.hk/publications/

• 👦 沈邵劼教授[谷歌学术](https://scholar.google.com/citations?user=u8Q0_xsAAAAJ&hl=zh-CN)

• 代码公开地址：https://github.com/HKUST-Aerial-Robotics

• 📜 Qin T, Li P, Shen S. [Vins-mono: A robust and versatile monocular visual-inertial state estimator](https://arxiv.org/pdf/1708.03852.pdf)[J]. IEEE Transactions on Robotics, 2018, 34(4): 1004-1020.（代码：https://github.com/HKUST-Aerial-Robotics/VINS-Mono ）

• 📜 Wang K, Gao F, Shen S. [Real-time scalable dense surfel mapping](https://arxiv.org/pdf/1909.04250)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 6919-6925.（代码：https://github.com/HKUST-Aerial-Robotics/DenseSurfelMapping ）

32. 香港科技大学机器人与多感知实验室 RAM-LAB

Note

• 研究方向：无人车；无人船；室内定位；机器学习。

• 实验室主页：https://www.ram-lab.com/

• 发表论文：https://www.ram-lab.com/publication/

• 👦 刘明教授[谷歌学术](https://scholar.google.com/citations?user=CdV5LfQAAAAJ&hl=zh-CN&oi=sra)

• 📜 Ye H, Chen Y, Liu M. [Tightly coupled 3d lidar inertial odometry and mapping](https://arxiv.org/pdf/1904.06993.pdf)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 3144-3150.（代码：https://github.com/hyye/lio-mapping ）

• 📜 Zhang J, Tai L, Boedecker J, et al. [Neural slam: Learning to explore with external memory]()[J]. arXiv preprint arXiv:1706.09520, 2017.

33. 香港中文大学天石机器人实验室

Note

• 研究方向：工业、物流、手术机器人，三维影像，机器学习

• 实验室主页：http://ri.cuhk.edu.hk/

• 👦 刘云辉教授：http://ri.cuhk.edu.hk/yhliu

• 👦 李浩昂：[个人主页](https://sites.google.com/view/haoangli/homepage)，[谷歌学术](https://scholar.google.com/citations?user=KnnPc0YAAAAJ&hl=zh-CN&oi=sra)

• 📜 Li H, Yao J, Bazin J C, et al. [A monocular SLAM system leveraging structural regularity in Manhattan world](http://cvrs.whu.edu.cn/projects/Struct-PL-SLAM/source/file/Struct_PL_SLAM.pdf)[C]//2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018: 2518-2525.

• 📜 Li H, Yao J, Lu X, et al. [Combining points and lines for camera pose estimation and optimization in monocular visual odometry](https://ieeexplore.ieee.org/abstract/document/8202304/)[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017: 1289-1296.

• 📜 消失点检测：Lu X, Yaoy J, Li H, et al. [2-Line Exhaustive Searching for Real-Time Vanishing Point Estimation in Manhattan World](https://www.computer.org/csdl/proceedings/wacv/2017/4822/00/07926628.pdf)[C]//Applications of Computer Vision (WACV), 2017 IEEE Winter Conference on. IEEE, 2017: 345-353.（代码：https://github.com/xiaohulugo/VanishingPointDetection ）

• 👦 郑帆：[个人主页](https://fzheng.me/cnabout/)，[谷歌学术](https://scholar.google.com/citations?user=PZOTyfIAAAAJ&hl=zh-CN&oi=sra)

• 📜 Zheng F, Tang H, Liu Y H. [Odometry-vision-based ground vehicle motion estimation with se (2)-constrained se (3) poses](https://ieeexplore.ieee.org/abstract/document/8357438/)[J]. IEEE transactions on cybernetics, 2018, 49(7): 2652-2663.（代码：https://github.com/izhengfan/se2clam ）

• 📜 Zheng F, Liu Y H. [Visual-Odometric Localization and Mapping for Ground Vehicles Using SE (2)-XYZ Constraints](https://ieeexplore.ieee.org/abstract/document/8793928/)[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 3556-3562.（代码：https://github.com/izhengfan/se2lam ）

34. 浙江大学 CAD&CG 国家重点实验室

Note

• 研究方向：SFM/SLAM，三维重建，增强现实

• 实验室主页：http://www.zjucvg.net/

• Github 代码地址：https://github.com/zju3dv

• 👦 章国峰教授：[个人主页](http://www.cad.zju.edu.cn/home/gfzhang/)，[谷歌学术](https://scholar.google.com/citations?user=F0xfpXAAAAAJ&hl=zh-CN&oi=sra)

• 📜 ICE-BA：Liu H, Chen M, Zhang G, et al. [Ice-ba: Incremental, consistent and efficient bundle adjustment for visual-inertial slam](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_ICE-BA_Incremental_Consistent_CVPR_2018_paper.pdf)[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018: 1974-1982.（代码：https://github.com/zju3dv/EIBA ）

• 📜 RK-SLAM：Liu H, Zhang G, Bao H. [Robust keyframe-based monocular SLAM for augmented reality](https://ieeexplore.ieee.org/abstract/document/7781760/)[C]//2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE, 2016: 1-10.（项目主页：http://www.zjucvg.net/rkslam/rkslam.html ）

• 📜 RD-SLAM：Tan W, Liu H, Dong Z, et al. [Robust monocular SLAM in dynamic environments](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.431.8137&rep=rep1&type=pdf)[C]//2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE, 2013: 209-218.

35. 邹丹平（上海交通大学）

Note

• 研究方向：视觉 SLAM，SFM，多源导航，微型无人机

• 👦 个人主页：http://drone.sjtu.edu.cn/dpzou/index.php ， [谷歌学术](https://scholar.google.com/citations?user=y6FsLDQAAAAJ&hl=en&oi=ao)

• 📜 Co-SLAM：Zou D, Tan P. [Coslam: Collaborative visual slam in dynamic environments](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.463.8135&rep=rep1&type=pdf)[J]. IEEE transactions on pattern analysis and machine intelligence, 2012, 35(2): 354-366.（代码：https://github.com/danping/CoSLAM ）

• 📜 StructSLAM：Zhou H, Zou D, Pei L, et al. [StructSLAM: Visual SLAM with building structure lines]()[J]. IEEE Transactions on Vehicular Technology, 2015, 64(4): 1364-1375.（项目主页：http://drone.sjtu.edu.cn/dpzou/project/structslam.php ）

• 📜 StructVIO：Zou D, Wu Y, Pei L, et al. [StructVIO: visual-inertial odometry with structural regularity of man-made environments](https://arxiv.org/pdf/1810.06796)[J]. IEEE Transactions on Robotics, 2019, 35(4): 999-1013.

36. 布树辉教授（西北工业大学智能系统实验室

Note

• 研究方向：语义定位与建图、SLAM、在线学习与增量学习

• 👦 个人主页：http://www.adv-ci.com/blog/ &emsp; [谷歌学术](https://scholar.google.com/citations?user=spwZ6b4AAAAJ&hl=zh-CN&oi=ao)

• 布老师的课件：http://www.adv-ci.com/blog/course/

• 实验室 2018 年暑期培训资料：https://github.com/zdzhaoyong/SummerCamp2018

• 📜 开源的通用 SLAM 框架：Zhao Y, Xu S, Bu S, et al. [GSLAM: A general SLAM framework and benchmark](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zhao_GSLAM_A_General_SLAM_Framework_and_Benchmark_ICCV_2019_paper.pdf)[C]//Proceedings of the IEEE International Conference on Computer Vision. 2019: 1110-1120.（代码：https://github.com/zdzhaoyong/GSLAM ）

• 📜 Bu S, Zhao Y, Wan G, et al. [Map2DFusion: Real-time incremental UAV image mosaicing based on monocular slam](http://www.adv-ci.com/publications/2016_IROS.pdf)[C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016: 4564-4571.（代码：https://github.com/zdzhaoyong/Map2DFusion ）

• 📜 Wang W, Zhao Y, Han P, et al. [TerrainFusion: Real-time Digital Surface Model Reconstruction based on Monocular SLAM](https://ieeexplore.ieee.org/abstract/document/8967663/)[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019: 7895-7902.

+1 Cyrill Stachniss（德国波恩大学摄影测量与机器人实验室）

Note

• 研究方向：概率机器人、SLAM、自主导航、视觉激光感知、场景分析与分配、无人飞行器

• 实验室主页：https://www.ipb.uni-bonn.de/

• 👦 个人主页：https://www.ipb.uni-bonn.de/people/cyrill-stachniss/ [谷歌学术](https://scholar.google.com/citations?user=8vib2lAAAAAJ&hl=zh-CN&authuser=1&oi=ao)

• 发表论文：https://www.ipb.uni-bonn.de/publications/

• 开源代码：https://github.com/PRBonn

• 📜 IROS 2019 激光语义 SLAM：Chen X, Milioto A, Palazzolo E, et al. [SuMa++: Efficient LiDAR-based semantic SLAM](https://ieeexplore.ieee.org/abstract/document/8967704/)[C]//2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019: 4530-4537.（代码：https://github.com/PRBonn/semantic_suma/ ）

• Cyrill Stachniss 教授 SLAM 公开课：[youtube](https://www.youtube.com/watch?v=4QG0y0pIOBE&list=PLgnQpQtFTOGQh_J16IMwDlji18SWQ2PZ6) ； [bilibili](https://space.bilibili.com/16886998/channel/detail?cid=118821)

• 波恩大学另外一个**智能自主系统实验室**：http://www.ais.uni-bonn.de/research.html

+1 上海科技大学

Note

• Mobile Perception Lab：http://mpl.sist.shanghaitech.edu.cn/

• 👦 Laurent Kneip：[个人主页](https://www.laurentkneip.com/)；[谷歌学术](https://scholar.google.com.au/citations?user=lTmh1e0AAAAJ&hl=en)

• 📜 Zhou Y, Li H, Kneip L. [Canny-vo: Visual odometry with rgb-d cameras based on geometric 3-d–2-d edge alignment](https://ieeexplore.ieee.org/abstract/document/8510917/)[J]. IEEE Transactions on Robotics, 2018, 35(1): 184-199.

• 自主移动机器人实验室：https://robotics.shanghaitech.edu.cn/zh

• 👦 Sören Schwertfeger：[个人主页](https://robotics.shanghaitech.edu.cn/zh/people/soeren)；[谷歌学术](https://scholar.google.com.au/citations?user=Y2olJ9kAAAAJ&hl=en&oi=ao)

• 📜 Shan Z, Li R, Schwertfeger S. [RGBD-Inertial Trajectory Estimation and Mapping for Ground Robots](https://link.zhihu.com/?target=https%3A//www.mdpi.com/1424-8220/19/10/2251)[J]. Sensors, 2019, 19(10): 2251.（代码：https://github.com/STAR-Center/VINS-RGBD ）

+1 美国密歇根大学机器人研究所

Note

• 学院官网：https://robotics.umich.edu/

• 研究方向：https://robotics.umich.edu/research/focus-areas/

• 感知机器人实验室（PeRL）

• 实验室主页：http://robots.engin.umich.edu/About/

• 👦 Ryan M. Eustice [谷歌学术](https://scholar.google.com/citations?user=WroYmiAAAAAJ&hl=en&oi=ao)

• 📜 激光雷达数据集 Pandey G, McBride J R, Eustice R M. [Ford campus vision and lidar data set](https://journals.sagepub.com/doi/abs/10.1177/0278364911400640)[J]. The International Journal of Robotics Research, 2011, 30(13): 1543-1552. | [数据集](http://robots.engin.umich.edu/SoftwareData/Ford)

• APRIL robotics lab

• 实验室主页：https://april.eecs.umich.edu/

• 👦 Edwin Olson [个人主页](https://april.eecs.umich.edu/people/ebolson/) | [谷歌学术](https://scholar.google.com/citations?user=GwtVjKYAAAAJ&hl=en&oi=ao)

• 📜 Olson E. [AprilTag: A robust and flexible visual fiducial system](https://april.eecs.umich.edu/pdfs/olson2010tags.pdf)[C]//2011 IEEE International Conference on Robotics and Automation. IEEE, 2011: 3400-3407. | [代码](https://github.com/AprilRobotics/apriltag)

• 📜 Wang X, Marcotte R, Ferrer G, et al. [ApriISAM: Real-time smoothing and mapping](https://april.eecs.umich.edu/papers/details.php?name=wang2018aprilsam)[C]//2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018: 2486-2493. | [代码](https://github.com/xipengwang/AprilSAM)

+1 瑞士苏黎世联邦理工自主系统实验室

Note

• 研究方向：复杂多样环境中自主运行的机器人和智能系统

• 实验室主页：https://asl.ethz.ch/

• 发表论文：https://asl.ethz.ch/publications-and-sources/publications.html

• [youtube](https://www.youtube.com/channel/UCgqwlRBPdDL2k4OWvH6Oppg) | [Github](https://github.com/ethz-asl)

• 👦 Cesar Cadena [个人主页](http://n.ethz.ch/~cesarc/)

• 📜 Schneider T, Dymczyk M, Fehr M, et al. [maplab: An open framework for research in visual-inertial mapping and localization](https://arxiv.org/pdf/1711.10250)[J]. IEEE Robotics and Automation Letters, 2018, 3(3): 1418-1425. | [代码](https://github.com/ethz-asl/maplab)

• 📜 Dubé R, Cramariuc A, Dugas D, et al. [SegMap: 3d segment mapping using data-driven descriptors](https://arxiv.org/pdf/1804.09557)[J]. arXiv preprint arXiv:1804.09557, 2018. | [代码](https://github.com/ethz-asl/segmap)

• 📜 Millane A, Taylor Z, Oleynikova H, et al. [C-blox: A scalable and consistent tsdf-based dense mapping approach](https://arxiv.org/pdf/1710.07242)[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 995-1002. | [代码](https://github.com/ethz-asl/cblox)

+1 美国麻省理工学院 Robust Robotics Group

Note

• 研究方向：MAV 导航与控制；人机交互的自然语言理解；自主海洋机器人的语义理解

• 实验室主页：http://groups.csail.mit.edu/rrg/index.php

• 👦 Nicholas Roy：[Google Scholar](https://scholar.google.com/citations?user=aM3i_9oAAAAJ&hl=zh-CN&oi=ao)

• 📜 Greene W N, Ok K, Lommel P, et al. [Multi-level mapping: Real-time dense monocular SLAM](https://ieeexplore.ieee.org/abstract/document/7487213/)[C]//2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2016: 833-840. [video](https://www.youtube.com/watch?v=qk2ViPVxmq0&feature=youtu.be)

• 📜 ICRA 2020 [Metrically-Scaled Monocular SLAM using Learned Scale Factors.” International Conference on Robotics and Automation](http://groups.csail.mit.edu/rrg/papers/greene_icra20.pdf) | [video](https://www.youtube.com/watch?v=qk2ViPVxmq0&feature=youtu.be)

• 📜 ICRA 2019 [Robust Object-based SLAM for High-speed Autonomous Navigation](http://groups.csail.mit.edu/rrg/papers/OkLiu19icra.pdf)

+1 瑞士苏黎世联邦理工 Vision for Robotics Lab

Note

• 研究方向：机器人视觉，无人机，自主导航，多机器人协同

• 实验室主页：https://v4rl.ethz.ch/the-group.html

• 👦 Margarita Chli：[个人主页](http://www.margaritachli.com/) | [Google Scholar](https://scholar.google.com/citations?user=C0UhwEIAAAAJ&hl=zh-CN&oi=ao)

• 📜 Schmuck P, Chli M. [CCM‐SLAM: Robust and efficient centralized collaborative monocular simultaneous localization and mapping for robotic teams](https://onlinelibrary.wiley.com/doi/full/10.1002/rob.21854)[J]. Journal of Field Robotics, 2019, 36(4): 763-781. [code](https://github.com/VIS4ROB-lab/ccm_slam) | [video](https://www.youtube.com/watch?v=P3b7UiTlmbQ&feature=youtu.be)

• 📜 Bartolomei L, Karrer M, Chli M. [Multi-robot Coordination with Agent-Server Architecture for Autonomous Navigation in Partially Unknown Environments](https://www.research-collection.ethz.ch/handle/20.500.11850/441280)[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020)(virtual). 2020. [code](https://github.com/VIS4ROB-lab/multi_robot_coordination) | [video](https://www.youtube.com/watch?v=ATQiTsbaSOw)

• 📜 Schmuck P, Chli M. [Multi-uav collaborative monocular slam](https://ieeexplore.ieee.org/abstract/document/7989445/)[C]//2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2017: 3863-3870.

+1 谢立华教授（南洋理工大学

Note

• 研究方向：控制，多智能体，定位

• 个人主页：https://personal.ntu.edu.sg/elhxie/research.html | [Google Scholar](https://scholar.google.com.hk/citations?user=Fmrv3J8AAAAJ&hl=zh-CN&oi=ao)

• 👦 Wang Han：[个人主页](https://wanghan.pro/) | [Github](https://github.com/wh200720041)

• 📜 Wang H, Wang C, Xie L. [Intensity scan context: Coding intensity and geometry relations for loop closure detection](https://ieeexplore.ieee.org/abstract/document/9196764/)[C]//2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2020: 2095-2101. | [Code](https://github.com/wh200720041/iscloam)

• 📜 Wang H, Wang C, Xie L. [Lightweight 3-D Localization and Mapping for Solid-State LiDAR](https://ieeexplore.ieee.org/abstract/document/9357899/)[J]. IEEE Robotics and Automation Letters, 2021, 6(2): 1801-1807. | [Code](https://github.com/wh200720041/ssl_slam)

• 📜 Wang C, Yuan J, Xie L. [Non-iterative SLAM](https://ieeexplore.ieee.org/abstract/document/8023500/)[C]//2017 18th International Conference on Advanced Robotics (ICAR). IEEE, 2017: 83-90.

3.SLAM 学习资料

1 国内资料

Note

• 1) SLAMcn：http://www.slamcn.org/index.php/

• 2) SLAM 最新研究更新 Recent_SLAM_Research ：https://github.com/YiChenCityU/Recent_SLAM_Research

• 3) 西北工大智能系统实验室 SLAM 培训：https://github.com/zdzhaoyong/SummerCamp2018

• 布树辉老师课件：http://www.adv-ci.com/blog/course/

• 4) IROS 2019 **视觉惯导导航**的挑战与应用研讨会：http://udel.edu/~ghuang/iros19-vins-workshop/index.html

• 5) 泡泡机器人 VIO 相关资料：https://github.com/PaoPaoRobot/Awesome-VIO

• 6) 崔华坤：主流 VIO 论文推导及代码解析：https://github.com/StevenCui/VIO-Doc

• 7) 李言：[SLAM 中的几何与学习方法](https://github.com/yanyan-li/SLAM-BOOK)

• 8) 黄山老师状态估计视频：[bilibili](https://www.bilibili.com/video/av66258275)

• 9) 谭平老师-SLAM 6小时课程：[bilibili](https://www.bilibili.com/video/BV1v4411p735)

• 10) 2020 年 SLAM 技术及应用暑期学校：[视频-bilibili](https://www.bilibili.com/video/BV1Hf4y1X7P5/) | [课件](http://www.cad.zju.edu.cn/home/gfzhang/download/2020-SLAM-Summer-School-slides.zip)

2 国外资料

Note

• 1) **事件相机**相关研究与发展：https://github.com/uzh-rpg/event-based_vision_resources

• 2) 加州大学圣地亚哥分校**语境机器人研究所** Nikolay Atanasov 教授**机器人状态估计与感知课程** ppt：https://natanaso.github.io/ece276a2019/schedule.html

• 3) 波恩大学 Mobile Sensing and Robotics Course 公开课 ：[youtube](https://www.youtube.com/playlist?list=PLgnQpQtFTOGQJXx-x0t23RmRbjp_yMb4v) ，[bilibili](https://space.bilibili.com/16886998/channel/detail?cid=118821)

3 公众号

Note

• 泡泡机器人 SLAM：paopaorobot_slam

4 代码注释

Note

今天（2020.04.25）刚想到的一个点，就算前面整理了大量的开源工作，但是看原版的代码还是会有很大的困难，感谢国内 SLAM 爱好者的将自己的代码注释分享出来，促进交流，共同进步。这一小节的内容陆续发掘，期待大家的推荐代码注释（可以在 issue 中留言）。

5 数据集

Note

• [泡泡机器人 - SLAM 数据集合集](https://mp.weixin.qq.com/s/zRjwus68Kf4unIqPIubraw)

• [计算机视觉life - SLAM、重建、语义相关数据集大全](https://zhuanlan.zhihu.com/p/68294012)

• [水下 SLAM 相关研究 - 代码、数据集](http://note.youdao.com/s/GjCXvWFR)

4.Optimization

• 后端优化库 GTSAM g2o ceres

• ICE-BA

• 因子图最小二乘优化框架 minisam

• 几何基元图优化 SA-SHAGO

• SLAM优化器 MH-iSAM2

• 用于定位和建图的模块化优化框架 MOLA

开源公告

• 既授人以鱼，亦授人以渔

• 鱼渔皆俱，实则授业解惑也

• 愿众薪拾火，成大业之道不久矣

Contact Me

If you use learn more xslam knowledge, please contact me:

author: Du Yongquan
email: quandy2020@126.com

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