ROS Resources: Documentation | Support | Discussion Forum | Index | Service Status | ros @ Robotics Stack Exchange
Ask Your Question
0

Why" The origin for the sensor at is out of map bounds" warning after configuring roboot_localization

asked 2022-02-07 14:16:37 -0500

chm007 gravatar image

updated 2022-02-25 04:13:14 -0500

Tom Moore gravatar image

Hi all,

I added an IMU to improve odometery and used robot_localozation to fuze odom and IMU data. I speficied the initial pose in ekf configs but my robot wont get its initial pose on the map properly. If I rum move_base not without robot_localization locates to its initial pose just fine on the map. How can I get it to position to its initial pose on the map when its using robot_localization??

Below you will my ekf config file, my cosmap files local and global and launch file for move base.

EKF config:

frequency: 30

silent_tf_failure: false

two_d_mode: true

transform_time_offset: 0.5

transform_timeout: 0.5

print_diagnostics: true

debug: false

publish_tf: true

publish_acceleration: false

map_frame: map              # Defaults to "map" if unspecified
odom_frame: odom            # Defaults to "odom" if unspecified
base_link_frame: base_link  # Defaults to "base_link" if unspecified
world_frame: map           # Defaults to the value of odom_frame if unspecified but if map specified USE MAP (Check AMCL)


odom0: /odom

odom0_config: [false, false,  false,
               false, false, false,
               true,  true,  false,
               false, false, true,
               false, false, false]


imu0: example/imu
imu0_config: [false, false, false,
              false, false, false,
              false, false, false,
              false, false,  true,
              true,  true,  false]

use_control: false

stamped_control: false


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]


initial_estimate_covariance: [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,     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,     0,    0,    0,
                              0,    0,    0,    0 ...
(more)
edit retag flag offensive close merge delete

Comments

You need a lot more information here:

  • What is generating the odom->base_link transform? Your EKF is just doing map->odom.
  • Are you using amcl or something? You can't have two nodes publishing the robot's map frame pose.

I think you should read REP-105, but then you need to give more detail about what nodes you are running.

Tom Moore gravatar image Tom Moore  ( 2022-02-25 04:18:20 -0500 )edit

@ Tom, Thank you for your response. I am actually using EKF for fusing sensors and AMCL for localization. Thanks to your response, I just realized that I have EKF publishing TF also. I will set this option to false and report back the results. Thanks again.

chm007 gravatar image chm007  ( 2022-03-03 18:52:30 -0500 )edit

OK, please don't forget to update this question with an answer when you have one.

Tom Moore gravatar image Tom Moore  ( 2022-03-17 06:19:53 -0500 )edit

1 Answer

Sort by ยป oldest newest most voted
0

answered 2022-03-18 15:35:33 -0500

chm007 gravatar image

updated 2022-03-18 15:36:38 -0500

Good Afternoon Tom,

Your suggestion to check which node were publishing was on point. I stopped EKF from publishing and all is working fine now. Thanks again.

edit flag offensive delete link more

Question Tools

1 follower

Stats

Asked: 2022-02-07 14:16:37 -0500

Seen: 146 times

Last updated: Feb 25 '22