From b5352f038608502cb2d698350d44f86d59416f9c Mon Sep 17 00:00:00 2001 From: "Juan D. Tardos" Date: Sun, 19 Jul 2020 10:42:19 +0200 Subject: [PATCH] Update README.md --- README.md | 47 +++++++++++++++++++++-------------------------- 1 file changed, 21 insertions(+), 26 deletions(-) diff --git a/README.md b/README.md index 856a9a8916..e765f4e633 100644 --- a/README.md +++ b/README.md @@ -3,46 +3,42 @@ ### V0.2: Beta version, 21 Jul 2020 **Authors:** [Carlos Campos], [Richard Elvira], [Juan J. Gómez], [Juan D. Tardos](http://webdiis.unizar.es/~jdtardos/), [J. M. M. Montiel](http://webdiis.unizar.es/~josemari/) -ORB-SLAM3 is a real time SLAM library for **Monocular**, **Stereo** and **RGB-D** sensors with capabilities to handle **Inertial** sensors and **Multiple-Maps**. The camera abstraction allow to work with different kind of camera, the code include the implementation of **Pinhole** and **Fisheye** sensors. This software is able to combine the diffenrent configurations to build a 3D sparse map where the main sensor is located. +ORB-SLAM3 is the first real time SLAM library able to perform **Visual, Visual-Inertial and Multi-Map SLAM** with **monocular, stereo and RGB-D** cameras, using **pin-hole and fisheye** lens models. In all sensor configurations, ORB-SLAM3 is as robust as the best systems available in the literature, and significantly more accurate. -We provide examples to run the SLAM system in the [EuRoC dataset](http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) as pinhole stereo or monocular with or without inertial measures, in the [TUM-VI dataset](https://vision.in.tum.de/data/datasets/visual-inertial-dataset) as fisheye stereo or monocular with or without inertial. +We provide examples to run ORB-SLAM3 system in the [EuRoC dataset](http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) using stereo or monocular with or without IMU, and in the [TUM-VI dataset](https://vision.in.tum.de/data/datasets/visual-inertial-dataset) using fisheye stereo or monocular with or without IMU. - -This code is the next version of ORB-SLAM2 developed by [Raul Mur-Artal](http://webdiis.unizar.es/~raulmur/), [Juan D. Tardos](http://webdiis.unizar.es/~jdtardos/), [J. M. M. Montiel](http://webdiis.unizar.es/~josemari/) and [Dorian Galvez-Lopez](http://doriangalvez.com/) ([DBoW2](https://github.com/dorian3d/DBoW2)) +This software is based on [ORB-SLAM2](https://github.com/raulmur/ORB_SLAM2) developed by [Raul Mur-Artal](http://webdiis.unizar.es/~raulmur/), [Juan D. Tardos](http://webdiis.unizar.es/~jdtardos/), [J. M. M. Montiel](http://webdiis.unizar.es/~josemari/) and [Dorian Galvez-Lopez](http://doriangalvez.com/) ([DBoW2](https://github.com/dorian3d/DBoW2)). ### Related Publications: -[ORB-SLAM3] Carlos Campos*, Richard Elvira*, Juan J. Gómez, J. M. M. Montiel and Juan D. Tardós. **ORB-SLAM3**. *Submited to IEEE Transactions on Robotics*. **[PDF](https://arxiv.org/pdf)**. -*Same contribution to the article. +Carlos Campos, Richard Elvira, Juan J. Gómez, J. M. M. Montiel and Juan D. Tardós, **ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM**, Under review. **[PDF](https://arxiv.org/pdf)**. + +[IMU-Initialization] Carlos Campos, J. M. M. Montiel and Juan D. Tardós, **Inertial-Only Optimization for Visual-Inertial Initialization**. *ICRA 2020*. **[PDF](https://arxiv.org/pdf/2003.05766.pdf)** -[Inertial-Initialization] Carlos Campos, J. M. M. Montiel and Juan D. Tardós. **Inertial-Only Optimization for Visual-Inertial Initialization**. *ICRA 2020*. **[PDF](https://arxiv.org/pdf/2003.05766.pdf)** +[ORBSLAM-Atlas] Richard Elvira, J. M. M. Montiel and Juan D. Tardós, **ORBSLAM-Atlas: a robust and accurate multi-map system**. *IROS 2019*. **[PDF](https://arxiv.org/pdf/1908.11585.pdf)**. -[ORBSLAM-Atlas] Richard Elvira, J. M. M. Montiel and Juan D. Tardós. **ORBSLAM-Atlas: a robust and accurate multi-map system**. *IROS 2019*. **[PDF](https://arxiv.org/pdf/1908.11585.pdf)**. +[ORBSLAM-VI] Raúl Mur-Artal, and Juan D. Tardós, **Visual-inertial monocular SLAM with map reuse**, IEEE Robotics and Automation Letters, vol. 2 no. 2, pp. 796-803, 2017. **[PDF](https://arxiv.org/pdf/1610.05949.pdf)**. -[Stereo and RGB-D] Raúl Mur-Artal and Juan D. Tardós. **ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras**. *IEEE Transactions on Robotics,* vol. 33, no. 5, pp. 1255-1262, 2017. **[PDF](https://128.84.21.199/pdf/1610.06475.pdf)**. +[Stereo and RGB-D] Raúl Mur-Artal and Juan D. Tardós. **ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras**. *IEEE Transactions on Robotics,* vol. 33, no. 5, pp. 1255-1262, 2017. **[PDF](https://arxiv.org/pdf/1610.06475.pdf)**. -[Monocular] Raúl Mur-Artal, J. M. M. Montiel and Juan D. Tardós. **ORB-SLAM: A Versatile and Accurate Monocular SLAM System**. *IEEE Transactions on Robotics,* vol. 31, no. 5, pp. 1147-1163, 2015. (**2015 IEEE Transactions on Robotics Best Paper Award**). **[PDF](http://webdiis.unizar.es/~raulmur/MurMontielTardosTRO15.pdf)**. +[Monocular] Raúl Mur-Artal, J. M. M. Montiel and Juan D. Tardós. **ORB-SLAM: A Versatile and Accurate Monocular SLAM System**. *IEEE Transactions on Robotics,* vol. 31, no. 5, pp. 1147-1163, 2015. (**2015 IEEE Transactions on Robotics Best Paper Award**). **[PDF](https://arxiv.org/pdf/1502.00956.pdf)**. -[DBoW2 Place Recognizer] Dorian Gálvez-López and Juan D. Tardós. **Bags of Binary Words for Fast Place Recognition in Image Sequences**. *IEEE Transactions on Robotics,* vol. 28, no. 5, pp. 1188-1197, 2012. **[PDF](http://doriangalvez.com/php/dl.php?dlp=GalvezTRO12.pdf)** +[DBoW2 Place Recognition] Dorian Gálvez-López and Juan D. Tardós. **Bags of Binary Words for Fast Place Recognition in Image Sequences**. *IEEE Transactions on Robotics,* vol. 28, no. 5, pp. 1188-1197, 2012. **[PDF](http://doriangalvez.com/php/dl.php?dlp=GalvezTRO12.pdf)** # 1. License -ORB-SLAM2 is released under a [GPLv3 license](https://github.com/UZ-SLAMLab/ORB_SLAM3/LICENSE). For a list of all code/library dependencies (and associated licenses), please see [Dependencies.md](https://github.com/UZ-SLAMLab/ORB_SLAM3/Dependencies.md). +ORB-SLAM3 is released under [GPLv3 license](https://github.com/UZ-SLAMLab/ORB_SLAM3/LICENSE). For a list of all code/library dependencies (and associated licenses), please see [Dependencies.md](https://github.com/UZ-SLAMLab/ORB_SLAM3/Dependencies.md). For a closed-source version of ORB-SLAM3 for commercial purposes, please contact the authors: orbslam (at) unizar (dot) es. -If you use ORB-SLAM2 (Monocular) in an academic work, please cite: - - @article{murTRO2015, - title={{ORB-SLAM3}:}, - author={Campos, Carlos, Elvira, Richard, G\´omez, Juan J., Montiel, J. M. M. and Tard\'os, Juan D.}, - journal={IEEE Transactions on Robotics}, - volume={}, - number={}, - pages={}, - doi = {}, - year={} +If you use ORB-SLAM3 in an academic work, please cite: + + @article{Campos2020, + title={{ORB-SLAM3}: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map {SLAM}}, + author={Campos, Carlos AND Elvira, Richard AND G\´omez, Juan J. AND Montiel, J. M. M. AND Tard\'os, Juan D.}, + journal={arXiv preprint arXiv:xxxx.yyyy}, + year={2020} } # 2. Prerequisites @@ -85,7 +81,7 @@ This will create **libORB_SLAM3.so** at *lib* folder and the executables in *Ex 1. Download a sequence (ASL format) from http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets -2. Execute the following first command to execute as pure visual , or the second command to visual-inertial. Change PATH_TO_SEQUENCE_FOLDER and SEQUENCE according to the sequence you want to run. +2. Execute the following first command to execute as pure visual, or the second command to visual-inertial. Change PATH_TO_SEQUENCE_FOLDER and SEQUENCE according to the sequence you want to run. ``` ./Examples/Monocular/mono_euroc Vocabulary/ORBvoc.txt Examples/Monocular/EuRoC.yaml PATH_TO_SEQUENCE_FOLDER/mav0/cam0/data Examples/Monocular/EuRoC_TimeStamps/SEQUENCE.txt ``` @@ -133,13 +129,12 @@ This will create **libORB_SLAM3.so** at *lib* folder and the executables in *Ex There is an executable to process a set of dataset sequentially, each dataset starts from scratch a new map. ## EuRoC Monocular + 1. Download a sequence (ASL format) from http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets 2. Execute the following command to execute for N dataset. Change PATH_TO_SEQUENCE_FOLDER_i and SEQUENCE_i according to the sequence you want to run. - - ## EuRoC Monocular-Inertial 1. Download a sequence (ASL format) from http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets