BITcats/basalt-mirror

Mirror of the Basalt repository. All pull requests and issues should be sent to https://gitlab.com/VladyslavUsenko/basalt

Basalt

For more information see https://vision.in.tum.de/research/vslam/basalt

This project contains tools for:

• Camera, IMU and motion capture calibration.
• Visual-inertial odometry and mapping.
• Simulated environment to test different components of the system.

Some reusable components of the system are available as a separate header-only library (Documentation).

There is also a Github mirror of this project to enable easy forking.

Related Publications

Visual-Inertial Odometry and Mapping:

• Visual-Inertial Mapping with Non-Linear Factor Recovery, V. Usenko, N. Demmel, D. Schubert, J. Stückler, D. Cremers, In IEEE Robotics and Automation Letters (RA-L) [DOI:10.1109/LRA.2019.2961227] [arXiv:1904.06504].

Calibration (explains implemented camera models):

• The Double Sphere Camera Model, V. Usenko and N. Demmel and D. Cremers, In 2018 International Conference on 3D Vision (3DV), [DOI:10.1109/3DV.2018.00069], [arXiv:1807.08957].

Calibration (demonstrates how these tools can be used for dataset calibration):

• The TUM VI Benchmark for Evaluating Visual-Inertial Odometry, D. Schubert, T. Goll, N. Demmel, V. Usenko, J. Stückler, D. Cremers, In 2018 International Conference on Intelligent Robots and Systems (IROS), [DOI:10.1109/IROS.2018.8593419], [arXiv:1804.06120].

Calibration (describes B-spline trajectory representation used in camera-IMU calibration):

• Efficient Derivative Computation for Cumulative B-Splines on Lie Groups, C. Sommer, V. Usenko, D. Schubert, N. Demmel, D. Cremers, In 2020 Conference on Computer Vision and Pattern Recognition (CVPR), [DOI:10.1109/CVPR42600.2020.01116], [arXiv:1911.08860].

Optimization (describes square-root optimization and marginalization used in VIO/VO):

• Square Root Marginalization for Sliding-Window Bundle Adjustment, N. Demmel, D. Schubert, C. Sommer, D. Cremers, V. Usenko, In 2021 International Conference on Computer Vision (ICCV), [arXiv:2109.02182]

Installation

APT installation for Ubuntu 20.04 and 18.04 (Fast)

Set up keys, add the repository to the sources list, update the Ubuntu package index and install Basalt:

sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys 0AD9A3000D97B6C9
sudo sh -c 'echo "deb [arch=amd64] http://packages.usenko.eu/ubuntu $(lsb_release -sc) $(lsb_release -sc)/main" > /etc/apt/sources.list.d/basalt.list'
sudo apt-get update
sudo apt-get dist-upgrade
sudo apt-get install basalt

Source installation for Ubuntu >= 18.04 and MacOS >= 10.14 Mojave

Clone the source code for the project and build it. For MacOS you should have Homebrew installed.

git clone --recursive https://gitlab.com/VladyslavUsenko/basalt.git
cd basalt
./scripts/install_deps.sh
mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=RelWithDebInfo
make -j8

Usage

• Camera, IMU and Mocap calibration. (TUM-VI, Euroc, UZH-FPV and Kalibr datasets)
• Visual-inertial odometry and mapping. (TUM-VI and Euroc datasets)
• Visual odometry (no IMU). (KITTI dataset)
• Simulation tools to test different components of the system.
• Batch evaluation tutorial (ICCV'21 experiments)

Device support

• Tutorial on Camera-IMU and Motion capture calibration with Realsense T265.

Development

• Development environment setup.

Licence

The code is provided under a BSD 3-clause license. See the LICENSE file for details. Note also the different licenses of thirdparty submodules.

Some improvements are ported back from the fork granite (MIT license).