{"id":14111264,"url":"https://github.com/Hardy-Uint/awesome-SLAM-algorithm","last_synced_at":"2025-08-01T12:31:57.465Z","repository":{"id":112508520,"uuid":"273134674","full_name":"Hardy-Uint/awesome-SLAM-algorithm","owner":"Hardy-Uint","description":"SLAM algorithm","archived":false,"fork":false,"pushed_at":"2023-05-30T11:08:41.000Z","size":10,"stargazers_count":16,"open_issues_count":0,"forks_count":8,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-04-11T22:04:43.236Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Hardy-Uint.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2020-06-18T03:40:54.000Z","updated_at":"2023-07-19T09:48:59.000Z","dependencies_parsed_at":"2024-01-16T01:25:19.947Z","dependency_job_id":"84a2ae4c-26c8-4724-9b1d-6064f3fe592e","html_url":"https://github.com/Hardy-Uint/awesome-SLAM-algorithm","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Hardy-Uint%2Fawesome-SLAM-algorithm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Hardy-Uint%2Fawesome-SLAM-algorithm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Hardy-Uint%2Fawesome-SLAM-algorithm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Hardy-Uint%2Fawesome-SLAM-algorithm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Hardy-Uint","download_url":"https://codeload.github.com/Hardy-Uint/awesome-SLAM-algorithm/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":228230850,"owners_count":17888706,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-14T10:03:13.362Z","updated_at":"2024-12-05T21:31:02.891Z","avatar_url":"https://github.com/Hardy-Uint.png","language":null,"readme":"\n\n# SLAM\n\n## 优秀开源项目汇总\n\n[https://github.com/OpenSLAM/awesome-SLAM-list](https://github.com/OpenSLAM/awesome-SLAM-list)\n\n[https://github.com/tzutalin/awesome-visual-slam](https://github.com/tzutalin/awesome-visual-slam)\n\nhttps://github.com/kanster/awesome-slam\n\nhttps://github.com/YoujieXia/Awesome-SLAM\n\n[Recent_SLAM_Research](https://github.com/YiChenCityU/Recent_SLAM_Research)\n\n[https://github.com/youngguncho/awesome-slam-datasets](https://github.com/youngguncho/awesome-slam-datasets)\n\n[https://github.com/marknabil/SFM-Visual-SLAM](https://github.com/marknabil/SFM-Visual-SLAM)\n\n[https://github.com/ckddls1321/SLAM_Resources](https://github.com/ckddls1321/SLAM_Resources)\n\n## 激光SLAM\n\n\u003e 分为前端和后端。其中前端主要完成匹配和位置估计，后端主要完成进一步的优化约束。\n\u003e\n\u003e 整个SLAM大概可以分为前端和后端，前端相当于VO（视觉里程计），研究帧与帧之间变换关系。首先提取每帧图像特征点，利用相邻帧图像，进行特征点匹配，然后利用RANSAC去除大噪声，然后进行匹配，得到一个pose信息（位置和姿态），同时可以利用IMU（Inertial measurement unit惯性测量单元）提供的姿态信息进行滤波融合。\n\u003e\n\u003e 后端则主要是对前端出结果进行优化，利用滤波理论（EKF、UKF、PF）、或者优化理论TORO、G2O进行树或者图的优化。最终得到最优的位姿估计。\n\n### 数据预处理\n\n### 点云匹配\n\n### 地图构建\n\n## 视觉SLAM\n\n### Books\n\n- [视觉SLAM十四讲]() 高翔\n- [机器人学中的状态估计]()\n- [概率机器人]()\n- [Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods](http://www.igi-global.com/book/simultaneous-localization-mapping-mobile-robots/66380) by Juan-Antonio Fernández-Madrigal and José Luis Blanco Claraco, 2012\n- [Simultaneous Localization and Mapping: Exactly Sparse Information Filters ](http://www.worldscientific.com/worldscibooks/10.1142/8145/)by Zhan Wang, Shoudong Huang and Gamini Dissanayake, 2011\n- [An Invitation to 3-D Vision -- from Images to Geometric Models](http://vision.ucla.edu/MASKS/) by Yi Ma, Stefano Soatto, Jana Kosecka and Shankar S. Sastry, 2005\n- [Multiple View Geometry in Computer Vision](http://www.robots.ox.ac.uk/~vgg/hzbook/) by Richard Hartley and Andrew Zisserman, 2004\n- [Numerical Optimization](http://home.agh.edu.pl/~pba/pdfdoc/Numerical_Optimization.pdf) by Jorge Nocedal and Stephen J. Wright, 1999\n\n### Courses\u0026\u0026Lectures\n\n- [SLAM Tutorial@ICRA 2016](http://www.dis.uniroma1.it/~labrococo/tutorial_icra_2016/)\n- [Geometry and Beyond - Representations, Physics, and Scene Understanding for Robotics](http://rss16-representations.mit.edu/) at Robotics: Science and Systems (2016)\n- [Robotics - UPenn](https://www.coursera.org/specializations/robotics) on Coursera by Vijay Kumar (2016)\n- [Robot Mapping - UniFreiburg](http://ais.informatik.uni-freiburg.de/teaching/ws15/mapping/) by Gian Diego Tipaldi and Wolfram Burgard (2015-2016)\n- [Robot Mapping - UniBonn](http://www.ipb.uni-bonn.de/robot-mapping/) by Cyrill Stachniss (2016)\n- [Introduction to Mobile Robotics - UniFreiburg](http://ais.informatik.uni-freiburg.de/teaching/ss16/robotics/) by Wolfram Burgard, Michael Ruhnke and Bastian Steder (2015-2016)\n- [Computer Vision II: Multiple View Geometry - TUM](http://vision.in.tum.de/teaching/ss2016/mvg2016) by Daniel Cremers ( Spring 2016)\n- [Advanced Robotics - UCBerkeley](http://www.cs.berkeley.edu/~pabbeel/) by Pieter Abbeel (Fall 2015)\n- [Mapping, Localization, and Self-Driving Vehicles](https://www.youtube.com/watch?v=x5CZmlaMNCs) at CMU RI seminar by John Leonard (2015)\n- [The Problem of Mobile Sensors: Setting future goals and indicators of progress for SLAM](http://ylatif.github.io/movingsensors/) sponsored by Australian Centre for Robotics and Vision (2015)\n- [Robotics - UPenn](https://alliance.seas.upenn.edu/~meam620/wiki/index.php?n=Main.HomePage) by Philip Dames and Kostas Daniilidis (2014)\n- [Autonomous Navigation for Flying Robots](http://vision.in.tum.de/teaching/ss2014/autonavx) on EdX by Jurgen Sturm and Daniel Cremers (2014)\n- [Robust and Efficient Real-time Mapping for Autonomous Robots](https://www.youtube.com/watch?v=_W3Ua1Yg2fk) at CMU RI seminar by Michael Kaess (2014)\n- [KinectFusion - Real-time 3D Reconstruction and Interaction Using a Moving Depth Camera](https://www.youtube.com/watch?v=bRgEdqDiOuQ) by David Kim (2012)\n\n### Code\n\n1. [ORB-SLAM](https://github.com/raulmur/ORB_SLAM)\n2. [LSD-SLAM](https://github.com/tum-vision/lsd_slam)\n3. [ORB-SLAM2](https://github.com/raulmur/ORB_SLAM2)\n4. [DVO: Dense Visual Odometry](https://github.com/tum-vision/dvo_slam)\n5. [SVO: Semi-Direct Monocular Visual Odometry](https://github.com/uzh-rpg/rpg_svo)\n6. [G2O: General Graph Optimization](https://github.com/RainerKuemmerle/g2o)\n7. [RGBD-SLAM](https://github.com/felixendres/rgbdslam_v2)\n\n| Project                                                      | Language | License                    |\n| ------------------------------------------------------------ | -------- | -------------------------- |\n| [COSLAM](http://drone.sjtu.edu.cn/dpzou/project/coslam.php)  | C++      | GNU General Public License |\n| [DSO-Direct Sparse Odometry](https://github.com/JakobEngel/dso) | C++      | GPLv3                      |\n| [DTSLAM-Deferred Triangulation SLAM](https://github.com/plumonito/dtslam) | C++      | modified BSD               |\n| [LSD-SLAM](https://github.com/tum-vision/lsd_slam/)          | C++/ROS  | GNU General Public License |\n| [MAPLAB-ROVIOLI](https://github.com/ethz-asl/maplab)         | C++/ROS  | Apachev2.0                 |\n| [OKVIS: Open Keyframe-based Visual-Inertial SLAM](https://github.com/ethz-asl/okvis) | C++      | BSD                        |\n| [ORB-SLAM](https://github.com/raulmur/ORB_SLAM2)             | C++      | GPLv3                      |\n| [REBVO - Realtime Edge Based Visual Odometry for a Monocular Camera](https://github.com/JuanTarrio/rebvo) | C++      | GNU General Public License |\n| [SVO semi-direct Visual Odometry](https://github.com/uzh-rpg/rpg_svo) | C++/ROS  | GNU General Public License |\n","funding_links":[],"categories":["Other Lists"],"sub_categories":["TeX Lists"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FHardy-Uint%2Fawesome-SLAM-algorithm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FHardy-Uint%2Fawesome-SLAM-algorithm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FHardy-Uint%2Fawesome-SLAM-algorithm/lists"}