软件
产品
本文简单将各种方案分为以下 7 类（固然有不少文章无法恰当分类，比如动态语义稠密建图的 VISLAM +_+）：
本文将列出15个Semantic/Deep SLAM开源方案和13个Multi-Landmarks/Object SLAM开源方案。
1. MsakFusion
· 论文：Runz M, Buffier M, Agapito L. Maskfusion: Real-time recognition, tracking and reconstruction of multiple moving objects[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[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[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[J]. arXiv preprint arXiv:1910.02490, 2019.
· 代码：https://github.com/MIT-SPARK/Kimera ；演示视频
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[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[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，演示视频
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[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. 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[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[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[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[J]. IEEE Robotics and Automation Letters, 2019, 4(4): 3505-3512.
· 代码：https://github.com/jiexiong2016/GCNv2_SLAM Video
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[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
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[C]. ICLR 2020.
· 代码：https://github.com/devendrachaplot/Neural-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[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[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[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[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[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[J]. IEEE Access, 2019, 7: 39923-39934.
· 代码：https://github.com/alexandervakhitov/lld-slam ；Video
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[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[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017: 1775-1782.
6. PlaneSLAM
· 论文：Wietrzykowski J. On the representation of planes for efficient graph-based slam with high-level features[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[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
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[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[C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016: 4602-4609.
· 代码：https://github.com/BeipengMu/objectSLAM ；Video
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[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[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。
· 也有很多有意思的但没开源的物体级 SLAM
o Ok K, Liu K, Frey K, et al. Robust Object-based SLAM for High-speed Autonomous Navigation[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 669-675.
o Li J, Meger D, Dudek G. Semantic Mapping for View-Invariant Relocalization[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 7108-7115.
o Nicholson L, Milford M, Sünderhauf N. Quadricslam: Dual quadrics from object detections as landmarks in object-oriented slam[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[J]. IEEE Access, 2020.
· 代码：https://bitbucket.org/hridaybavle/semantic_slam/src/master/
微信扫码，回复：开源SLAM，即可获取全文文档（共97个方案，本文28个）
免责声明：本文系网络转载或改编，未找到原创作者，版权归原作者所有。如涉及版权，请联系删
技术文档
热门文章
155-2731-8020
