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weihsinc/robot_localization: A ROS package for real-time nonlinear state estimat ...

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

weihsinc/robot_localization

开源软件地址(OpenSource Url):

https://github.com/weihsinc/robot_localization

开源编程语言(OpenSource Language):

C++ 97.1%

开源软件介绍(OpenSource Introduction):

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



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