setting covariances for robot_localization

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Hi all,

I have a mobile robot and I am using robot_localization to fuse data from wheel_encoders, IMU and hokuyo lidar (using AMCL). In the first instance of robot_localization, I have wheel_encoders and IMU in the odom_frame and in the second instance of robot_localization, I have wheel_encoders and output of AMCL (amcl_pose (geometry_msgs/PoseWithCovarianceStamped)) in the map_frame.

This is my launch file for the second instance of robot_localization :

<launch>

<node pkg="robot_localization" type="ekf_localization_node" name="ekf_localization2" clear_params="true">

  <param name="frequency" value="10"/>

  <param name="sensor_timeout" value="0.5"/>

  <param name="two_d_mode" value="true"/>

  <param name="map_frame" value="map"/>
  <param name="odom_frame" value="odom_combined"/>
  <param name="base_link_frame" value="base_footprint"/>
  <param name="world_frame" value="map"/>

  <param name="transform_time_offset" value="0.0"/>

  <param name="odom0" value="odom"/>
  <param name="pose0" value="amcl_pose"/>

  <rosparam param="odom0_config">[false, false, false,
                                  false, false, false,
                                  true, true, false,
                                  false, false, true,
                                  false, false, false]</rosparam>

  <rosparam param="pose0_config">[true,  true,  false,
                                  false, false, true,
                                  false, false, false,
                                  false, false, false,
                                  false, false, false]</rosparam>

  <param name="odom0_differential" value="true"/>
  <param name="pose0_differential" value="false"/>

  <param name="print_diagnostics" value="true"/>

  <param name="debug"           value="false"/>
  <param name="debug_out_file"  value="debug_ekf_localization.txt"/>

  <rosparam param="process_noise_covariance">[0.05, 0,    0,    0,    0,    0,    0,     0,     0,    0,    0,    0,    0,    0,    0,
                                              0,    0.05, 0,    0,    0,    0,    0,     0,     0,    0,    0,    0,    0,    0,    0,
                                              0,    0,    0.06, 0,    0,    0,    0,     0,     0,    0,    0,    0,    0,    0,    0,
                                              0,    0,    0,    0.03, 0,    0,    0,     0,     0,    0,    0,    0,    0,    0,    0,
                                              0,    0,    0,    0,    0.03, 0,    0,     0,     0,    0,    0,    0,    0,    0,    0,
                                              0,    0,    0,    0,    0,    0.06, 0,     0,     0,    0,    0,    0,    0,    0,    0,
                                              0,    0,    0,    0,    0,    0,    0.025, 0,     0,    0,    0,    0,    0,    0,    0,
                                              0,    0,    0,    0,    0,    0,    0,     0.025, 0,    0,    0,    0,    0,    0,    0,
                                              0,    0,    0,    0,    0,    0,    0,     0,     0.04, 0,    0,    0,    0,    0,    0,
                                              0,    0,    0,    0,    0,    0,    0,     0,     0,    0.01, 0,    0,    0,    0,    0,
                                              0,    0,    0,    0,    0,    0,    0,     0,     0,    0,    0.01, 0,    0,    0,    0,
                                              0,    0,    0,    0,    0,    0,    0,     0,     0,    0,    0,    0.02, 0,    0,    0,
                                              0,    0,    0,    0,    0,    0,    0,     0,     0,    0,    0,    0,    0.01, 0,    0,
                                              0,    0,    0,    0,    0,    0,    0,     0,     0,    0,    0,    0,    0,    0.01, 0,
                                              0,    0,    0,    0,    0,    0,    0,     0,     0,    0,    0,    0,    0,    0,    0.015]</rosparam>

       <rosparam param="initial_estimate_covariance">[0.3, 0,    0,    0,    0,    0,    0,    0,    0,    0,     0,     0,     0,    0,    0,
                                                      0,    0.3, 0,    0,    0,    0,    0,    0,    0,    0,     0,     0,     0,    0,    0,
                                                      0,    0,    1e-9, 0,    0,    0,    0,    0,    0,    0,     0,     0,     0,    0,    0,
                                                      0,    0,    0,    1e-9, 0,    0,    0,    0,    0,    0,     0,     0 ...