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I use ROS2/Python/Gazebo project. In online examples, I see robot_localization node using (usually in nav2_params.yaml) the "imu/data" as imu source. In the same time, all projects I got from the Internet, produce "imu" (no "data" part). Are these two the same? And how to "explain" it to robot_localization node:

    robot_localization_node = Node(
        package='robot_localization',
        executable='ekf_node',
        name='ekf_filter_node',
        namespace=namespace,
        output='screen',
        parameters=[ 
            os.path.join(def_bringup_dir, 'config', 'nav2_params.yaml'),
            {'use_sim_time': use_sim_time }],
        #remappings=[('odometry/filtered', 'odometry/filtered_no_gps'),
        #    ('/set_pose', '/initialpose')
        #]
    )  

So far, it doesn't publish odometry/filtered AT ALL. Plus, I cannot figure out what the commented out remappings are for.

Please help.

amcl: ros__parameters: set_initial_pose: true initial_pose: x: robot_pos_x y: robot_pos_y z: 0.1 yaw: 0.0

use_sim_time: True
alpha1: 0.002
alpha2: 0.002
alpha3: 0.002
alpha4: 0.002
alpha5: 0.002 
base_frame_id: "base_footprint"
odom_frame_id: "odom"
scan_topic: /scan
beam_skip_distance: 0.5
beam_skip_error_threshold: 0.9
beam_skip_threshold: 0.3
do_beamskip: false
global_frame_id: "map"
lambda_short: 0.1
laser_likelihood_max_dist: 2.0
laser_max_range: 100.0
laser_min_range: -1.0
laser_model_type: "likelihood_field"
map_frame: map
max_beams: 60
max_particles: 2000
min_particles: 500
pf_err: 0.05
pf_z: 0.99
recovery_alpha_fast: 0.0
recovery_alpha_slow: 0.0
resample_interval: 1
robot_model_type: "differential"
save_pose_rate: 0.5
sigma_hit: 0.2
tf_broadcast: true
transform_tolerance: 1.0
update_min_a: 0.2
update_min_d: 0.25
z_hit: 0.5
z_max: 0.05
z_rand: 0.5
z_short: 0.05

amcl_map_client: ros__parameters: use_sim_time: True

amcl_rclcpp_node: ros__parameters: use_sim_time: True

...

ekf_filter_node: ros__parameters:

    use_sim_time: true
    frequency: 30.0
    sensor_timeout: 0.1
    two_d_mode: true
    transform_time_offset: 0.0
    transform_timeout: 0.0
    print_diagnostics: true
    debug: false
    debug_out_file: /path/to/debug/file.txt
    publish_tf: true
    publish_acceleration: false
    reset_on_time_jump: true
    map_frame: map                   # Defaults to "map" if unspecified
    odom_frame: odom                 # Defaults to "odom" if unspecified
    base_link_frame: base_footprint  # Defaults to "base_link" if unspecified
    world_frame: odom                 # Defaults to the value of odom_frame if unspecified
    odom0: /odom
    odom0_config: [true, true, true,
                   false, false, false,
                   true,  true,  true,
                   false, false, true,
                   false, false, false]
    odom0_queue_size: 2
    odom0_nodelay: false
    odom0_differential: false
    odom0_relative: false
    odom0_pose_rejection_threshold: 5.0
    odom0_twist_rejection_threshold: 1.0

    imu0: /imu
    imu0_config: [false, false, false,
                  true,  true,  true,
                  false, false, false,
                  true,  true,  true,
                  true,  true,  true]
    imu0_nodelay: false
    imu0_differential: false
    imu0_relative: true
    imu0_queue_size: 7
    imu0_pose_rejection_threshold: 0.8                 # Note the difference in parameter names
    imu0_twist_rejection_threshold: 0.8                #
    imu0_linear_acceleration_rejection_threshold: 0.8  #
    imu0_remove_gravitational_acceleration: true
    use_control: false
    stamped_control: false
    control_timeout: 0.2
    control_config: [true, false, false, false, false, true]
    acceleration_limits: [1.3, 0.0, 0.0, 0.0, 0.0, 3.4]
    deceleration_limits: [1.3, 0.0, 0.0, 0.0, 0.0, 4.5]
    acceleration_gains: [0.8, 0.0, 0.0, 0.0, 0.0, 0.9]
    deceleration_gains: [1.0, 0.0, 0.0, 0.0, 0.0, 1.0]
    process_noise_covariance: [0.05,   0.0,    ..

    initial_estimate_covariance: [1e-9,   0.0,    ...

# navsat_transform:
#   ros__parameters:
#     use_sim_time: true
#     frequency: 10.0
#     delay: 3.0
#     magnetic_declination_radians: 0.093084220955  # For lat/long of Atlanta, Georgia
#     yaw_offset: 0.0  # if IMU reads 0 when facing magnetic north instead of east then set parameter to pi/2
#     zero_altitude: true
#     broadcast_utm_transform: true
#     broadcast_utm_transform_as_parent_frame: true
#     publish_filtered_gps: true
#     use_odometry_yaw: false
#     wait_for_datum: true
    
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1 Answer 1

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The message type is the same - it's just a different topic name/namespace. For a robot that only has a single topic carrying IMU data, "imu" might be sufficient. However, many robots end up having a whole IMU data pipeline - for instance, you might often find several different topics all namespaced under "imu":

  • imu/data - this might be the raw data coming out of the sensor.
  • imu/filtered - there might be a node that subscribes to imu/data, filters the data, and then publishes the new filtered data to imu/filtered.

As for the remappings - when someone wrote the "robot_localization" node, they set it up to publish to a topic called "odometry/filtered". Remapping then allows the node to publish to "odometry/filtered_no_gps" without recompiling the code with a new topic name. You might be interested to look at the remapping design doc for ROS 2.

As for data not coming out of the node - we'd need to look into your nav2_params.yaml because that is going to define some parameters, including the names of the topics the node is subscribing.

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  • $\begingroup$ Thank you. I have added ekf config to original message. Please note that I do not use GPS: I have it in my system, but I do not want it to be merged with other sensors. So I didn't include it to yaml file. $\endgroup$ Sep 18, 2023 at 15:36

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