Dataset conversions

This page gives instructions on how to convert robotics datasets between ROS 1 and ROS 2 bag files or live messages, MRPT’s cross-platform RawLog format, and the custom formats of popular robotics and computer vision datasets.

1. Dataset formats

Robotics datasets consist of sequences of raw sensory data as captured by a mobile robot, a vehicle, or just a hand-held device, as they move through the environment.

Each robotic framework or library has defined its own formats over time:

• ROS 1 introduced rosbags (~2007) as a binary serialization storage for heterogeneous ROS messages.

• ROS 2 (~2014) improved rosbags, which now can use different storage implementations (sqlite3, mcap), and are more efficient and flexible than older versions.

• MRPT, on which MOLA is internally based on, defined its own serialized dataset format (~2005) named RawLogs, which is ensured to be portable across operative systems, backwards compatible across MRPT versions, and processor architecture independent.

Note

Apart of these standardized formats, many robotic datasets have their own custom data layout (e.g. one binary file for each 3D LiDAR scan or image). MOLA makes easy reading them by providing adapter modules that can read the most popular datasets (see list) through unified C++ APIs (class mola::OfflineDatasetSource) or re-publishing them to ROS.

2. rosbag ⇒ rawlog

To convert a ROS bag into a RawLog, you need two items: - The program rosbag2rawlog, - And a configuration file specifying what ROS messages should be converted.

There are two versions of rosbag2rawlog and the correct one must be installed depending on whether you need to convert ROS 1 or ROS 2 bags:

ROS 2 bags

rosbag2rawlog for ROS 2 bags. It is shipped with the ROS package mrpt_rawlog so it can be installed with:

sudo apt install ros-${ROS_DISTRO}-mrpt-rawlog

ROS 1 bags

rosbag2rawlog for ROS 1 bags belongs to upstream MRPT, and it is generated only if ROS 1 is detected at cmake configuration time. You can either build MRPT from sources after activating your ROS 1 environment, or install the Ubuntu package mrpt-apps, which already ships rosbag2rawlog for Ubuntu versions <=22.04 (In Ubuntu 24.04, ROS 1 packages were removed upstream). To ensure having the latest version, consider installing it from the PPA.

Once you have rosbag2rawlog installed it can be invoked like:

rosbag2rawlog CLI arguments

$ rosbag2rawlog --help

USAGE:

  rosbag2rawlog  [-b <base_link>] [-w] -c <config.yml> -o
                  <dataset_out.rawlog> [--] [--version] [-h] <log.bag> ...


Where:

  -b <base_link>,  --base-link <base_link>
    Reference /tf frame for the robot frame (Default: 'base_link')

  -w,  --overwrite
    Force overwrite target file without prompting.

  -c <config.yml>,  --config <config.yml>
    (required)  Config yaml file (*.yml)

  -o <dataset_out.rawlog>,  --output <dataset_out.rawlog>
    (required)  Output dataset (*.rawlog)

  --,  --ignore_rest
    Ignores the rest of the labeled arguments following this flag.

  --version
    Displays version information and exits.

  -h,  --help
    Displays usage information and exits.

  <log.bag>  (accepted multiple times)
    (required)  Input bag files (required) (*.bag)

For example:

$ rosbag2rawlog -c config.yaml -o output.rawlog  input.mcap

With the config.yaml file created as explained below.

2.1. YAML config file format

rosbag2rawlog needs an input configuration file to determine what ROS messages in the bag are to be imported. The rest will be discarded, after emitting a warning to the terminal.

Example: basic Ouster LiDAR import

# Config file for rosbag2rawlog. It must contain a top-level "sensors" node
sensors:
  # Then, one node per sensor to convert. This name will be used as
  # sensorLabel in MRPT observations.
  lidar:
    # Type: C++ class name (see mrpt::obs)
    type: 'CObservationPointCloud'
    topic: '/ouster/points'
    # If uncommented, /tf data will be ignored for this sensor pose:
    #fixed_sensor_pose: "0 0 0 0 0 0"  # 'x y z yaw_deg pitch_deg roll_deg''

Example: Newer College Dataset import

# Config file for rosbag2rawlog. It must contain a top-level "sensors" node
sensors:
  # Then, one node per sensor to convert. This name will be used as
  # sensorLabel in MRPT observations.
  lidar:
    # Type: C++ class name (see mrpt::obs)
    type: 'CObservationPointCloud'
    # Parameters for this particular type of sensor.
    # Topic to subscribe for the pointcloud:
    topic: '/os_cloud_node/points'
    fixed_sensor_pose: "0 0 0 0 0 0"  # 'x y z yaw_deg pitch_deg roll_deg''

  cam0:
    type: 'CObservationImage'
    image_topic: '/alphasense_driver_ros/cam0/compressed'
    fixed_sensor_pose: "0 0 0 0 0 0"  # 'x y z yaw_deg pitch_deg roll_deg''

Example: LiDAR + wheels odometry from /odom

# Config file for rosbag2rawlog. It must contain a top-level "sensors" node
sensors:
  # Then, one node per sensor to convert. This name will be used as
  # sensorLabel in MRPT observations.
  lidar:
    # Type: C++ class name (see mrpt::obs)
    type: 'CObservationPointCloud'
    topic: '/ouster/points'
    # If uncommented, /tf data will be ignored for this sensor pose:
    #fixed_sensor_pose: "0 0 0 0 0 0"  # 'x y z yaw_deg pitch_deg roll_deg''
  odom:
    type: 'CObservationOdometry'
    topic: '/odom'

Example: LiDAR + wheels odometry from /tf

# Config file for rosbag2rawlog. It must contain a top-level "sensors" node
sensors:
  # Then, one node per sensor to convert. This name will be used as
  # sensorLabel in MRPT observations.
  lidar:
    # Type: C++ class name (see mrpt::obs)
    type: 'CObservationPointCloud'
    topic: '/ouster/points'
    # If uncommented, /tf data will be ignored for this sensor pose:
    #fixed_sensor_pose: "0 0 0 0 0 0"  # 'x y z yaw_deg pitch_deg roll_deg''

# If provided, odometry observations will be generated from /tf messages
# from `odom_frame_id` to `base_link` (frame_id can be changed via cli arguments):
odom_from_tf:
    sensor_label: 'odom'  # mandatory entry
    #odom_frame_id: '/odom'

3. rawlog ⇒ ROS

For ROS 1 and ROS 2.

Write me!

4. ROS1 ⇒ ROS2

One way to use rosbags from ROS 1 with MOLA is to port them to ROS 2 bags.

You can use the Python package rosbags to perform the conversion.

An alternative is to use rosbag2rawlog (the ROS 1 version!) to convert them to RawLogs, then use them as input to MOLA.

5. MOLA data set module ⇒ ROS

All you need is to put together a MOLA launch YAML file with:

• A dataset source module.

• The ros2bridge module.

and launch it using mola-cli. See existing ROS launch examples under ros2-launch (mola_demos package), with corresponding MOLA cli launch files in the mola-cli-launchs directory.

Example: play back a KITTI dataset sequence to ROS 2

ros2 launch mola_demos ros-kitti-play.launch.py kitti_sequence:=01

Result: the mola_viz GUI + RViz.