Robot_localization doesnt work with Rosbag file

edit

I want to fuse the visual odometry of my Intel Realsense T265 camera with the wheel odometry of my AGV (Mechanum wheels). I am using the ekf_node with default covariances and the default launch file on Ros2 Eloquent. (files at the bootom) If I do it on the Robot itself everything works fine. The output of "/odometry/filtered" works fine and everything is calculated as it should. Now the Problem: If I record the exact same data from the robot with a rosbag2 and than try to calculate Robot_localization on my VM the estimated position goes crazy (values over 40000 in x for example). I record everything with the rosbag, so there is no difference except for the not running ekf node of course.

As far as I tested the error occured everytime I try to the Visual odometry signal or if I run the ekf a second time after stopping. After a reboot of the VM the first run is working, if there is only the wheel_odometry signal in the ekf. I am not sure if that is related or random.

I already tried swapping odom0 with odom1 and trying out different combinations in the config matrices. Like fusing position from both or x from the one, y from the other. Just experiments. But nothing helped.

Is this a known issue? Did I miss a setting that I need to get this going? A colleague mentioned it could be an issue with the recorded time?

Thanks in advance!

The used Launchfile:

from launch import LaunchDescription
from ament_index_python.packages import get_package_share_directory
import launch_ros.actions
import os
import yaml
from launch.substitutions import EnvironmentVariable
import pathlib
import launch.actions
from launch.actions import DeclareLaunchArgument

def generate_launch_description():
return LaunchDescription([
    launch_ros.actions.Node(
        package='robot_localization',
        node_executable='ekf_node',
        node_name='ekf_filter_node',
        output='screen',
        parameters=[os.path.join(get_package_share_directory("robot_localization"), 'params', 'ekf_t265.yaml')],
       ),
])

yaml file:

### ekf config file ###
ekf_filter_node:
  ros__parameters:
    frequency: 30.0

    two_d_mode: true

    odom0: /odom     #wheel_odometry
    odom0_config: [false, false, false,
                   false, false, true,
                   false, false, false,
                   false, false, false,
                   false, false, false]

    odom0_differential: true

    odom1: /camera/odom/sample  #VIO
    odom1_config: [true, true, false,
                   false, false, false,
                   false, false, false,
                   false, false, false,
                   false, false, false]

    odom1_differential: true

    odom_frame: odom
    base_link_frame: odom_frame
    world_frame: odom
    publish_tf: true

Update according to comment: I changed the Frames. My TF Tree now looks like: odom -> base_link -> camera_pose_optical_frame. My base_link frame now is base_link which is also the child frame of the wheel_odometry. Furthermore the transform: base_link -> child_frame of the camera camera_pose_optical_frame should now be as you mentioned. I still get this Warning: Warning: Invalid frame ID "odom" passed to canTransform argument target_frame - frame does not exist

I hope I did not misunderstood or missed something from your comment.

Here is my yaml-file:

ekf_filter_node:
    ros__parameters:
        frequency: 30.0
        use_sim_time: true

        two_d_mode: true

        odom0: /odom
        odom0_config: [false, false, false,
                       false, false, false,
                       true, true, false,
                       false, false, false,
                       false, false, false]

        odom0_differential: false

        odom1: /camera/odom/sample
        odom1_config: [true, true, false,
                       false, false, true,
                       false, false, false,
                       false ...