Basalt

Original repository

This repository is a modified version of basalt_ros. We facilitate the installation process and the use of Docker.

Docker support

In order to facilitate the installation process, the system is wrapped up using Docker. We provide scripts to create a Docker image, build the system and run it in a Docker container.

Dependencies

• Docker
• ROS
• pose_listener (if you use run_rosario_sequence.sh, see below)

Building the system

Run:

./run.sh -b

This command creates a Docker image, installs all the dependencies and builds the system. The resulting image contains a version of the system ready to be run.

Running the system in VIS mode

If you are not interested in making changes in the source code, you should run the system in VIS mode. Run:

./run.sh -v

The system is launched in a Docker container based on the previously built image. By default, this command executes a launch file which is configured to run the Rosario dataset. If you want to run your own dataset, write a launch file and placed it in basalt_ros1/launch/. Configuration files must be placed in basalt_ros1/config/. Then, run the script with the option -l <LAUNCH_FILE_NAME>. For example, if you are testing EuRoC, write euroc_dataset.launch, move it into basalt_ros1/launch/ and type:

./run.sh -v -l euroc_dataset.launch

Making changes in launch/configuration files in the host is possible because these folders are mounted into the Docker container. It is not necessary to access the container through a bash shell to modify these files.

See below for information about input data and visualization.

Running the system in DEV mode

DEV mode allows developers to make changes in the source code, recompile the system and run it with the modifications. To do this, the whole repository is mounted in a container. Run:

./run.sh -d

This opens a bash shell in a docker container. You can edit source files in the host and after that you can use this shell to recompile the system. When the compilation process finishes, you can run the method using roslaunch.

See below for information about input data and visualization.

Input data and visualization

At this point, the system is waiting for input data. Either you can run rosbag play or you can use run_rosario_sequence.sh. If you choose the latter, open a second terminal and run:

./run_rosario_sequence.sh -o <OUTPUT_TRAJECTORY_FILE> <ROSBAG_FILE>

In contrast to what run.sh does, run_rosario_sequence.sh executes commands in the host (you can modify it to use a Docker container).

ROSBAG_FILE is played using rosbag. Also, make sure you have cloned and built pose_listener in your catkin workspace. Default path for the workspace is ${HOME}/catkin_ws, set CATKIN_WS_DIR if the workspace is somewhere else (e.g.: export CATKIN_WS_DIR=$HOME/foo_catkin_ws). pose_listener saves the estimated trajectory in <OUTPUT_TRAJECTORY_FILE> (use absolute path). You can edit run_rosario_sequence.sh if you prefer to save the trajectory using your own methods. Additionally, run_rosario_sequence.sh launches rviz to display visual information during the execution of the system.

Alternatively, if you are not interested in development but in testing or visualization, instead of running run.sh and run_rosario_sequence.sh in two different terminals, you can just run:

./run_rosario_sequence.sh -r -o <OUTPUT_TRAJECTORY_FILE> <ROSBAG_FILE>

This launches a Docker container and executes the default launch file (see LAUNCH_FILE in run.sh). After that, the bagfile is played and rviz and pose_listener are launched. Add -b if you want to turn off the visualization.