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https://github.com/Taeyoung96/SLAM-Resources-for-Beginner

Highly recommended resources for SLAM newbies (Lecture, Reviewed paper, Books, Tutorial, etc)
https://github.com/Taeyoung96/SLAM-Resources-for-Beginner

List: SLAM-Resources-for-Beginner

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Highly recommended resources for SLAM newbies (Lecture, Reviewed paper, Books, Tutorial, etc)

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README 

        
# SLAM-Resources-for-Beginner



SLAM is an abbreviation for **"Simultaneous localization and mapping"**.  



SLAM is a field with high entry barriers for beginners.  



As a beginner learning SLAM, I created this repository to organize resources that can be used as a reference when learning SLAM for the first time.  



I made this repository based on the content from the [SLAM KR community](https://www.facebook.com/groups/slamkr/) and the activities of [my github followers](https://github.com/Taeyoung96?tab=following)!  



If you are Korean, you will prefer to look [korean.md](https://github.com/Taeyoung96/SLAM-Resources-for-Beginner/blob/master/korean.md).  



## Contents  



- [Mathematics](#Mathematics)  

- [Roadmap](#Roadmap)  

- [Review Paper & Survey Paper](#review-paper--survey-paper)  

- [Lecture](#Lecture)  

- [Books](#Books)  

- [Awesome-list](#Awesome-list)  

- [Recommended github repository](#Recommended-github-repository)  



## Mathematics  



- Some Math Basics often used in Photogrammetry (Cyrill Stachniss, 2021) [[Youtube](https://youtu.be/Q042jupFMbU)]    

> An brief, informal collection of math basics and tools that are often used in Photogrammetry (SVD, Least Squares with Gauss Newton)  



- Linear Algebra Primer - Stanford Vision Lab [[pdf](http://vision.stanford.edu/teaching/cs131_fall1617/lectures/lecture2_linalg_review_cs131_2016.pdf)]  

> Lecture slide for Linear Algebra Review  



## Roadmap



- [changh95/visual-slam-roadmap](https://github.com/changh95/visual-slam-roadmap)  

> Roadmap to becoming a Visual-SLAM developer  



## Review Paper & Survey Paper    



### SLAM  



- **"SLAM tutorial : Part 1"** By H. Durrant-Whyte and T. Bailey (IEEE Robotics & Automation Magazine 2006) - [[pdf](https://www.doc.ic.ac.uk/~ajd/Robotics/RoboticsResources/SLAMTutorial1.pdf)]

- **"SLAM tutorial : Part 2"** By H. Durrant-Whyte and T. Bailey (IEEE Robotics & Automation Magazine 2006) - [[pdf](https://www.doc.ic.ac.uk/~ajd/Robotics/RoboticsResources/SLAMTutorial2.pdf)]  

- **"Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age"** By C. Cadena et al. (IROS 2016) - [[pdf](http://rpg.ifi.uzh.ch/docs/TRO16_cadena.pdf)]  

- **"Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving"** By G. Bresson, Z. Alsayed et al. (IEEE Transactions on Intelligent Vehicles 2017) - [[pdf](https://hal.archives-ouvertes.fr/hal-01615897/file/2017-simultaneous_localization_and_mapping_a_survey_of_current_trends_in_autonomous_driving.pdf)]  

- **"Comparison of modern open-source visual SLAM approaches"** By Dinar Sharafutdinov et al. (ArXiv 2021) - [[pdf](https://arxiv.org/pdf/2108.01654.pdf)]



### Visual SLAM & Visual Odometry  



- **"Visual Odometry Part I: The First 30 Years and Fundamentals"** By Davide Scaramuzza and Friedrich Fraundorfer - [[pdf](http://rpg.ifi.uzh.ch/docs/VO_Part_I_Scaramuzza.pdf)]  

- **"Visual Odometry Part II: Matching, Robustness, Optimization, and Applications"** By Davide Scaramuzza and Friedrich Fraundorfer - [[pdf](http://rpg.ifi.uzh.ch/docs/VO_Part_II_Scaramuzza.pdf)]  

- **"A Comparison of Modern General-Purpose Visual SLAM Approaches"** By Alexey Merzlyakov et al. (IROS 2021) - [[pdf](https://arxiv.org/abs/2107.07589)]  



### Visual-Inertial SLAM  



- **"Visual-Inertial Navigation: A Concise Review"** By Guoquan Huang (ICRA 2019) - [[pdf](https://arxiv.org/abs/1906.02650)]  

- **"Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle"** By Jinwoo Jeon et al. (ArXiv 2021) - [[pdf](https://arxiv.org/abs/2103.01655)]  



### SLAM with Deep-learning  



- **"A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence"** By Changhao Chen et al. - [[pdf](https://arxiv.org/abs/2006.12567)]  



### LiDAR global localization  



- **"A Survey on Global LiDAR Localization: Challenges, Advances and Open Problems"** By Huan Yin et al. - [[pdf](https://arxiv.org/abs/2302.07433)]



## Lecture  



- **Mobile Robotics course** for the Winter 2020 Semester at the University of Michigan - [[Webpage](http://robots.engin.umich.edu/mobilerobotics/?fbclid=IwAR1NcjOxtgv6ohDPxFkAXIMDn91933IgGSXvav0HpO8lBWwCP0agFkoUS5A#lectures)]  

- **Mobile Sensing And Robotics 2** By Stachniss (2021) - [[Webpage](https://www.ipb.uni-bonn.de/msr2-2021/)]  

- **AirLab Summer School 2020** in Carnegie Mellon university - [[Webpage](https://theairlab.org/summer2020/)]  

- **Tartan SLAM Series** in AirLab - [[Webpage](https://theairlab.org/tartanslamseries/)]  

- **Tartan SLAM Series Fall Edition** in AirLab - [[Webpage](https://theairlab.org/tartanslamseries2/)]  



## Books 



- **Probabilistic Robotics** By Sebastian Thrun, Wolfram Burgard and Dieter Fox - [[Webpage](https://mitpress.mit.edu/books/probabilistic-robotics)], [[pdf](https://docs.ufpr.br/~danielsantos/ProbabilisticRobotics.pdf)]  

- **Computer Vision: Algorithms and Applications, 2nd ed.** By Richard Szeliski - [[Webpage](http://szeliski.org/Book/)]  

- **STATE ESTIMATION FOR ROBOTICS** By Timothy D. Barfoot - [[pdf](http://asrl.utias.utoronto.ca/~tdb/bib/barfoot_ser17.pdf)]  



## Awesome-list  

- [Awesome-SLAM](https://github.com/SilenceOverflow/Awesome-SLAM)  

- [awesome-visual-slam](https://github.com/tzutalin/awesome-visual-slam)  

- [Awesome LIDAR](https://github.com/szenergy/awesome-lidar)  

- [Awesome SLAM Datasets](https://github.com/youngguncho/awesome-slam-datasets)  

- [awesome-photogrammetry](https://github.com/awesome-photogrammetry/awesome-photogrammetry)  

- [Awesome Robotic Tooling](https://github.com/protontypes/awesome-robotic-tooling#simultaneous-localization-and-mapping)  

- [Awesome Robot Operating System 2 (ROS 2)](https://github.com/fkromer/awesome-ros2)  

- [awesome-modern-cpp](https://github.com/rigtorp/awesome-modern-cpp) : Modern C++ is important language to learn SLAM system.  



## Recommended github repository  



### SLAM Trend

- [YiChenCityU/Recent_SLAM_Research](https://github.com/YiChenCityU/Recent_SLAM_Research)  

> This repository tracks advancement of SLAM system. (2021 ver)  



### Visual SLAM  



- [gaoxiang12/slambook-en](https://github.com/gaoxiang12/slambook-en)  

> The English version of 14 lectures on visual SLAM. You could see source code in [Slambook2](https://github.com/gaoxiang12/slambook2).  



- [luigifreda/pyslam](https://github.com/luigifreda/pyslam)  

> pySLAM contains a monocular Visual Odometry (VO) pipeline in Python.  



- [avisingh599/mono-vo](https://github.com/avisingh599/mono-vo)  

> An OpenCV based implementation of Monocular Visual Odometry  



### Lidar SLAM

- [Kitware/pyLiDAR-SLAM](https://github.com/Kitware/pyLiDAR-SLAM)  

> This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods.



- [gisbi-kim/PyICP-SLAM](https://github.com/gisbi-kim/PyICP-SLAM)  

> Full-python LiDAR SLAM using ICP and Scan Context  



### Robotics  

- [AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics)  

> Python sample codes for robotics algorithms.  



- [rlabbe/Kalman-and-Bayesian-Filters-in-Python](https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python)  

> Kalman Filter book using Jupyter Notebook.  



### 3D Vision  

- [sunglok/3dv_tutorial](https://github.com/sunglok/3dv_tutorial)  

> An Invitation to 3D Vision: A Tutorial for Everyone