Go to file
Vladyslav Usenko 1ee6ca8294 small changes in Cmake 2019-06-18 15:16:24 +02:00
cmake_modules cmake: more strictly enforce finding the included eigen version 2019-05-13 21:41:00 +02:00
data Added Realsense live VIO 2019-06-13 11:37:17 +00:00
doc Switched to HashBow instead of DBoW3 2019-06-07 12:42:18 +00:00
docker updated docker images 2019-06-13 16:17:55 +02:00
include/basalt rename device 2019-06-13 18:21:37 +02:00
scripts Added Realsense live VIO 2019-06-13 11:37:17 +00:00
src small changes in Cmake 2019-06-18 15:16:24 +02:00
test switched to other test discovery 2019-06-07 16:25:21 +02:00
thirdparty small changes in Cmake 2019-06-18 15:16:24 +02:00
.clang-format add ./scripts/clang-format-all.sh and fix formatting 2019-04-24 13:16:06 +02:00
.gitignore Added development documentation. 2019-05-15 11:28:35 +02:00
.gitlab-ci.yml Disable Debug symbols in CI to reduce the ccache size 2019-06-09 18:49:03 +00:00
.gitmodules removed data submodule 2019-06-10 22:15:26 +02:00
CMakeLists.txt updated docker images 2019-06-13 16:17:55 +02:00
LICENSE Initial commit 2019-04-14 21:08:32 +02:00
README.md Added development documentation. 2019-05-15 11:28:35 +02:00

README.md

pipeline status

Basalt

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

teaser

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 availble as a separate header-only library.

Visual-Inertial Odometry and Mapping:

  • Visual-Inertial Mapping with Non-Linear Factor Recovery, V. Usenko, N. Demmel, D. Schubert, J. Stückler, D. Cremers, In [arXiv:1904.06504].

Calibration (explains implemented camera models):

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].

Installation

APT installation for Ubuntu 16.04 and 18.04 (Fast)

Set up keys

sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 0D97B6C9

Add the repository to the sources list. On Ubuntu 18.04 run:

sudo sh -c 'echo "deb [arch=amd64] http://packages.usenko.eu/ubuntu bionic main" > /etc/apt/sources.list.d/basalt.list'

On Ubuntu 16.04 run:

sudo sh -c 'echo "deb [arch=amd64] http://packages.usenko.eu/ubuntu xenial main" > /etc/apt/sources.list.d/basalt.list'

Update the Ubuntu package index and install Basalt:

sudo apt-get update
sudo apt-get install basalt

Source installation for Ubuntu 18.04 and MacOS >= 10.11 El Capitan

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

NOTE: It is possible to compile the code on Ubuntu 16.04, but you need to install cmake-3.10 or higher and gcc-7. See corresponding Dockerfile as an example.

Usage

Development

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.