Super comprehensive summary | related improvement codes of orb-slam2 / orb-slam3!

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Author Xiaoshen

Source: Shenzhen dialect AI

This paper summarizes the characteristic point method SLAM The best way to do this at present ：ORB-SLAM2 / ORB-SLAM3 Summary of relevant improvement codes , Including acceleration 、 Multi-sensor fusion 、 Dense mapping 、 Line features 、 Point line fusion 、 Navigation 、 Dynamic environment 、 Multi platform migration, etc . See below for details . 

For the convenience of clicking on the link , We've sorted it out pdf edition , Reply in the official account background ：ORBSLAM

ORB-SLAM2 Summary of relevant improvement codes

The paper was published in 2017 Year of IEEE Transactions on Robotics, Title of thesis 《ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras》

ORB-SLAM2 characteristic ：

• One of the first （2017 When it was released in ） Support single item , Eyes and RGB-D Camera's complete open source SLAM programme , It has the function of loop detection and relocation .

• In the CPU Work in real time on , It can be used for mobile terminals, such as Mobile robots 、 mobile phone 、 Unmanned aerial vehicle (uav) 、 automobile .

• The pinnacle of the characteristic point method , High positioning accuracy , Up to centimeter level .

• It can calculate the pose of the camera in real time , And generate sparse 3D reconstruction map of the scene .

• The code is very clean , Contains many practical skills , Very practical .

• Location only mode is supported , This mode is suitable for lightweight and long-term operation when the map is known , At this time, the threads of local mapping and loop back detection are not used

[PAPER](https://arxiv.org/abs/1610.06475),

[CODE](https://github.com/raulmur/ORB_SLAM2),

[ Super detailed Chinese annotation version ]

(https://github.com/electech6/ORBSLAM2_detailed_comments)

How to improve

[ORBSLAM2_with_pointcloud_map](https://github.com/gaoxiang12/ORBSLAM2_with_pointcloud_map),

Add dense point cloud map realized by Gao Xiang

[ORB-SLAM2_RGBD_DENSE_MAP]

(https://github.com/tiantiandabaojian/ORB-SLAM2_RGBD_DENSE_MAP), Dense closed-loop map is added on the basis of Gao Xiang

[ORB-YGZ-SLAM]

(https://github.com/gaoxiang12/ORB-YGZ-SLAM),

Use SVO Instead of the time-consuming feature point extraction and matching , With the same accuracy , It's primitive ORB-SLAM2 Fast 3 times

[YGZ-stereo-inertial SLAM]

(https://github.com/gaoxiang12/ygz-stereo-inertial),

Binocular VIO edition , Joined the LK Optical flow and sliding window BA Optimize

[VI-ORB](https://github.com/jingpang/LearnVIORB),

Jingpang realized VI-ORB-SLAM2

[Fisheye-ORB-SLAM]

(https://github.com/lsyads/fisheye-ORB-SLAM), Added support for fisheye

[Save and load orb-slam2 maps]

(https://github.com/AlejandroSilvestri/osmap), Add save and import map functions

[ORB_SLAM2 with map load/save function]

(https://github.com/Jiankai-Sun/ORB_SLAM2_Enhanced), Add save and import map functions

[Viewer for maps from ORB-SLAM2 Osmap]

(https://github.com/AlejandroSilvestri/Osmap-viewer),

Added map visualization

[Add line feature based ORB-SLAM2]

(https://github.com/atlas-jj/ORB_Line_SLAM), Added line features

[RGBD-SLAM with Point and Line Features, developed based on ORB_SLAM2]

(https://github.com/maxee1900/RGBD-PL-SLAM), Added point line fusion

[Good Feature Selection for Least Squares Pose Optimization in VO/VSLAM]

(https://github.com/ivalab/gf_orb_slam2), A better feature selection method is used

[ORB_SLAM2_SSD_Semantic](https://github.com/Ewenwan/ORB_SLAM2_SSD_Semantic), 

Dynamic semantics SLAM object detection +VSLAM+ Optical flow / Multi view geometric dynamic object detection +octomap Map + Target database

[Tracking Enhanced ORB-SLAM2]

(https://github.com/Eralien/TE-ORB_SLAM2),

use YOLO v3 To increase tracking performance

[YOLO Dynamic ORB_SLAM](https://github.com/bijustin/YOLO-DynaSLAM), use YOLO To detect the dynamic environment

Multi platform porting code

[Windows version ORBSLAM2,Easy built by visual studio]

(https://github.com/phdsky/ORBSLAM24Windows),

Windows Platform version , It can be used visual studio Easy to compile

[ORB-SLAM-Android, test on Sony Xperia Z]

(https://github.com/castoryan/ORB-SLAM-Android),

Android transplant , stay Sony Xperia Up test

[ORBSLAM2 on Mac OSX]

(https://github.com/meiroo/ORBSLAM2-OSX),Mac OSX edition

[ROS interface for ORBSLAM2]

(https://github.com/ethz-asl/orb_slam_2_ros), add to ROS Interface

ORB-SLAM3 Related codes

ORB-SLAM3

2020 year 07 In open source , The paper 《ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM》

ORB-SLAM3 characteristic

• Support vision 、 Visual plus inertial navigation 、 Mixed map SLAM System , It can be used in monocular , Eyes and RGB-D Use a pinhole or fish eye model to run on the camera .

• Feature based tightly coupled VIO System , It only depends on the maximum a posteriori estimation ( Include IMU On initialization ). So whether it's a big scene or a small scene , Robust real-time operation both indoors and outdoors , The accuracy is improved compared with the previous version 2 To 5 times

• A multi map system based on the new relocation module , It can make the system run for a long time in scenarios with poor characteristics .

• The first system to be able to reuse all previous information at all algorithmic stages , Can be in BA Use common view keyframes that are far apart .

[PAPER](https://arxiv.org/pdf/2007.11898.pdf)

[CODE](https://github.com/UZ-SLAMLab/ORB_SLAM3)

ORB_SLAM3-RGBD-Inertial

Added RGBD-IMU The mode of operation and ROS Interface , Added monocular IMU And the eyes IMU Of ROS Interface , Replace the dictionary with binary format , Faster loading . basis ORB_SLAM3 Rewrote RGBD-IMU Of ROS Interface , Avoid queue congestion , Provides Kinect for Azure Parameter file of

[CODE](https://github.com/xiefei2929/ORB_SLAM3-RGBD-Inertial)

This article is only for academic sharing , If there is any infringement , Please contact to delete .

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