libCML is a SLAM library and scientific tool, which include a novel fast thread-safe graph map implementation. It is used by MOD SLAM : a mixed method for a more robust SLAM without loop closing, that is implemented on this repository. You can find the paper here : Paper link : https://hal.archives-ouvertes.fr/hal-03538133.

If you want to make your own SLAM based on libCML, follow the tutorial here : under construction.

If you want to build the GUI, you will need Qt6 with Qt Multimedia and Qt Charts. Otherwise, please disable it with the according option (see below).

We recommend you to use CLion from Jetbrains, or Qt Creator from Nokia, to build and test. Otherwise, you can :

mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make -j 4

This is a list of different option you can pass to cmake :

-DENABLE_GUI=OFF # Disable/Enable the gui
-DUSE_GOOGLE_HASH=ON # Disable/Enable Google Hash Map. Enabling this option cause the map to take more memory, but to be faster.
-DENABLE_OPENMP=OFF # Disable/Enable OpenMP

We recommend you to use Qt Creator, as it is the most simple way to build ModSLAM on Android and iPhone.

1. Download and Install Android Studio
2. Download and Install JDK 17 (Higher version not supporter for the moment)
3. Download and Install Qt (with QtCreator, Qt 6 for Android, Qt Multimedia and Qt Charts)
4. Launch Qt Creator. Go to Android settings. Make sure that all is ok. Download the Android SDK you want.
5. Open the project with Qt Creator, configure it for Android/Release and simply build it

cd build
./modslam -d PATH_TO_THE_DATASET

where PATH_TO_THE_DATASET can be any dataset (TUM, KITTI, RobotCar, a mkv/mp4/avi/other video file...). MODSLAM will automatically detect the right dataset format.

Here is a list of arguments you can pass to the executable :

-c configfile.yaml # Load a specific config file
-g # Use Gui Mode
-t # Use Terminal Mode
-r path_to_result -f [tum|kitti|all] # Save the results with the specified format
-l log.txt # Write the log to a file
-s path_to_images # Export the 3D rendering to a ton of .jpeg files at specified folder
-z # Print the statistics at each iteration. Used for python script and result analasys.

Download here : https://www.cvlibs.net/datasets/kitti/eval_odometry.php

• Gray Scale Required
• Color Optional
• Groundtruth Optional

/KITTI
├── dataset
│   ├── poses
│   │   ├── 00.txt
│   │   ├── 01.txt
│   │   ├── 02.txt
│   │   ├── 03.txt
│   │   ├── 04.txt
│   │   ├── 05.txt
│   │   ├── 06.txt
│   │   ├── 07.txt
│   │   ├── 08.txt
│   │   ├── 09.txt
│   │   └── 10.txt
│   └── sequences
│       ├── 00
│       ├── 01
│       ├── 02
│       ├── 03
│       ├── 04
│       ├── 05
│       ├── 06
│       ├── 07
│       ├── 08
│       ├── 09
│       ├── 10

To run MOD SLAM on KITTI Odometry, you can use the following command :

cd build
./modslam -d /KITTI/dataset/sequences/02

/Stereopolis
├── Camera_0.zip
├── Camera_0.gt.txt
├── Camera_0.mask.png
├── Camera_0.times.txt
├── Camera_0.xml

To run MOD SLAM on Stereopolis, you can use the following command :

cd build
./modslam -d /Stereopolis/Camera_0.zip

cd result
python3 statson.py # Compute the absolute trajectory error of each videos
python3 bruteforce.py # Make statistics for the parameters / Search for a better parameters set
python3 make2dtable.py # Make a 2D table of the variation of ATE between by varying two parameters

The configuration file evaluation/config.txt contains the SLAMs and the datasets to evaluate on :

ModSLAM "../cmake-build-release/modslam"
TUM "/home/thomas/Datasets/TUM"
KITTI "/home/thomas/Datasets/KITTI"

The configuration file evaluation/modslam.yaml is the SLAM configuration you want to initialize the python script with.

Each result is stored in a .json file. Experience are never run twice. If a the result of an experience is already present in the .json file, the experience will not run a second time. You can plot all the result stored in the json database :

python3 plotall.py

All the result are stored in a result folder. This is the kind of result you can except with a few experiences :

This is a bug of Qt. Please use at least Qt 6.3.0.

This can be cause when you use the 32 bits of the compiler instead of the 64. Please read https://cmake.org/cmake/help/git-stage/guide/user-interaction/index.html for more details.