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ROS simulation for Neobotix mobile robots

This simulation package provides a quick and easy way to try out the autonomous mobile robots from Neobotix. It comes with the most commonly used configuration but is open for any kind of modification.

neo_simulation

Neobotix offers a wide range of mobile robots for different applications:

  • MP-400: Small and cost-saving robot with differential drive for both industrial transport applications and research.
  • MP-500: Compact, industrial grade robot for material flow and intralogistics. Very good system for robotics research when equipped with a robot arm.
  • MPO-500: Omnidirectional robot with Mecanum wheels for all kinds of service robotics research
  • MPO-700: Omnidirectional robot with Omni-Drive-Modules, offering very high payload and smooth movements. Great for both research and demanding industrial applications.

Contact information

For more information please visit our website at www.neobotix-robots.com. If you have any questions, just get in touch with us:

neo_simulation

Instructions to Download the Package

  1. First step is to create a catkin workspace

    Follow this link to create a workspace http://wiki.ros.org/catkin/Tutorials/create_a_workspace

  2. Next step is to clone the neo_simulation repository to the source folder of the created workspace(catkin_ws).

    $ cd catkin_ws/src

    $ git clone https://github.com/neobotix/neo_simulation.git

    once cloned go back to catkin_ws directory and run:

    $ catkin_make

    $ source devel/setup.bash

  3. Now we need to add the path of our custom gazebo models into the bashrc

    i. In your command line terminal

     $ gedit ~/.bashrc

    ii. Add this to your bashrc

     $ export GAZEBO_MODEL_PATH=/(Path to your workspace)/src/neo_simulation/models:$GAZEBO_MODEL_PATH

  4. Download additional Gazebo Models from http://data.nvision2.eecs.yorku.ca/3DGEMS/

Additional Packages that are required for the simulation

  1. Teleoperation
$ sudo apt-get install ros-kinetic-teleop-twist-keyboard
  1. Control package
$ sudo apt-get install ros-kinetic-ros-control
  1. Navigation
$ sudo apt-get install ros-kinetic-navigation

3.1 Local Planner

$ sudo apt-get install ros-kinetic-eband-local-planner

3.2 Localization

$ sudo apt-get install ros-kinetic-openslam-gmapping
$ sudo apt-get install ros-kinetic-amcl
  1. Scan Unifier (Just the folder cob_scan_unifier)
$ git clone https://github.com/neobotix/neo_driver.git

Launch a mobile Robot

To simulate the robot in gazebo run:

roslaunch neo_simulation simulation.launch

Parameters

Parameter Description Options
robot_type robot type used in simulation mpo_500, mmo_500, mpo_700
robot_world name of the .world file located in folder "worlds" neo_track1, neo_track2
rviz indicates if rviz should be started with the simulation true, false
autonomous_navigation indicates if move base and gmapping or amcl should be started with the simulation true, false

Moving obstacles

For neo_track2 world, there is a ready made python script for moving obstacles.

After launching the simulation for the mobile robot, run the following line in the command line window.

$ rosrun neo_simulation models_spawn.py

Topics

  1. /cmd_vel

    • Plugin name: Planar Move (geometry_msgs/twist)

    NOTE: With this the robot can move in all directions and also able rotate along the Z-direction.

  2. /sick_s300_laser/back/scan (sensor_msgs/LaserScan)

    • Frame name: sick_s300_laser_back_link

    • Plugin name: GPU Laser

    NOTE: Laser scan covers an angle of 270 degrees

  3. /sick_s300_laser/front/scan (sensor_msgs/LaserScan)

    • Frame name: sick_s300_laser_front_link

    • Plugin name: GPU Laser

    NOTE: Laser scan covers an angle of 270 degrees

  4. map (nav_msgs/OccupancyGrid)

    NOTE: This topic publishes the data of the map.

  5. amcl_pose (geometry_msgs/PoseWithCovarianceStamped)

    NOTE: This topic gives the estimated pose of the robot on map.

  6. tf (tf2_msgs/TFMessage)

    NOTE: This topic publishes transform from /odom to /map.

  7. particle cloud (geometry_msgs/PoseArray)

    NOTE: This topic publishes a set of pose estimates.