robot_localization
robot_localization is a ROS package of nonlinear state estimation nodes.
For detailed information please see documentation: http://wiki.ros.org/robot_localization
Installation
Requires "geographic-msgs". If not installed:
sudo apt-get install ros-indigo-geographic-msgs
How to run it?
Launch sensor drivers:
roslaunch robot_localization ekf_sensors.launch
- This launches the drivers for sensors that are fused by the filter. (tachometer, IMU and GPS)
Launch dual EKF:
roslaunch robot_localization dual_ekf.launch rviz_odom:=<true/false(default)> rviz_utm:=<true/false(default)>
- This launches two EKF nodes and tf publishers.
- ekf_local: EKF node for local pose estimation.
- ekf_global: EKF node for global pose estimation.
- args: rviz_odom (ekf_odom.rviz); rviz_utm (ekf_utm.rviz).
Launch global EKF:
roslaunch robot_localization ekf_global.launch rviz:=<true/false(default)>
- This launches global EKF localization node, ekf_global.
- args: rviz (ekf_utm.rviz).
Launch local EKF:
roslaunch robot_localization ekf_local.launch rviz:=<true/false(default)>
- This launches local EKF localization node, ekf_local.
- args: rviz (ekf_odom.rviz).
Visualization during operation:
roslaunch robot_localization rviz.launch
- This launches two RVIZ windows for visualizing 3D pose and odometry with respective configuration files.
- ekf_odom.rviz: RVIZ for local odometry. (grid reference frame: odom)
- ekf_utm.rviz: RVIZ for global odometry. (grid reference frame: gps_init_ENU)
Initialization
WARNING: At launching, the global pose estimation is undetermined until the vehicle starts driving for some distance. For details about sensor fusion layout, please refer to the Google slide: Local and Global Pose Estimation for Yamaha Viking
Subscribed topics
The ekf_odom node subscribes to
- /imu/data (sensor_msgs/Imu): Roll/Pitch/Yaw and Roll/Pitch/Yaw rates measurements from Xsens IMU.
- /vehicle_state/velocity (nav_msgs/Odometry): Vehicle forward velocity measurement from wheel encoder.
The ekf_map node subscribes to
- /imu/data (sensor_msgs/Imu): Roll/Pitch (NOTE: Not using IMU's yaw measurement in global EKF node) and Roll/Pitch/Yaw rates measurements from Xsens IMU.
- /vehicle_state/velocity (nav_msgs/Odometry): Vehicle forward velocity measurement from wheel encoder.
- /garmin_gps/odom (nav_msgs/Odometry): Absolute position in UTM coordinates from Garmin GPS.
Published topics
The ekf_odom node publishes
- /odometry/filtered_odom (nav_msgs/Odometry): Local pose estimation
- /tf (geometry_msgs/TransformStamped): Transforms from odom_frame to base_link_frame.
The ekf_map node publishes
- /odometry/filtered_map (nav_msgs/Odometry): Global pose estimation
- /tf (geometry_msgs/TransformStamped): Transforms from map_frame to odom_frame.
Parameters
All the parameters for the dual EKF are set up in the params/dual_ekf.yaml, please refer to the template file params/ekf_template.yaml or see the online documentation http://docs.ros.org/indigo/api/robot_localization/html/ for the definitions and usage on parameters.
Debugging
To debug the EKF pose on live test, use the following command
roslaunch robot_localization debug.launch
- This launches the rpy_publisher and the rqt_gui console with rqt_plot plugins for visualizing the time series of live message data.
Data Logging
To log a ros bag for EKF, use the launch file launch/ekf_log.launch. The launch file has already included the default topics needed, specify the path and file prefix in the "args" tag before recording a bag and use the following command
roslaunch robot_localization ekf_log.launch