Skip to content

fbk-pso/leo_navigation_tutorial

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

40 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

leo_navigation

This package was created as part of the Autonomous Navigation tutorial for Leo Rover. It provides configuration for SLAM and autonomous navigation for Leo Rover equipped with IMU and LiDAR sensors.

Launch files

  • odometry.launch

    Starts the ekf_localization_node from robot_localization which publishes the odometry based on Wheel encoders and IMU readings.

    Arguments:

    • three_d (default: false)

      If set to true, also starts imu_filter_madgwick to fuse data from IMU sensor into an orientation and uses it in the ekf_localization_node to provide a 3D odometry.

  • gmapping.launch

    Starts the slam_gmapping node from gmapping package which provides a laser-based SLAM.

  • amcl.launch

    Starts map_server which publishes static map from a file on a ROS topic and amcl which uses odometry and data from the LiDAR sensor to estimate the localization of the robot on the map.

    Arguments:

    • map_file (required)

      An absolute path to the map file in the format supported by map_server.

  • twist_mux.launch

    Starts twist_mux node which multiplexes several sources of velocity commands for the robot, giving priority to manual control over autonomous.

    Arguments:

    • cmd_vel_out (default: cmd_vel)

      The topic name the multiplexer should publish velocity commands on.

  • move_base.launch

    Starts move_base node which, given the robot's localization, a map of obstacles, laser scans and a navigation goal, plans a safe path to the goal and tries to execute it, by sending velocity commands to the robot.

  • navigation.launch

    Starts twist_mux.launch and move_base.launch.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • CMake 100.0%