Demos on Gazebo

Before running the demos it is necessary to get acquainted with the setup section of the documentation. Make sure you check: Using only the simulated robot

Launching the Simulation

1. Clone the robotont_gazebo package into your workspace:

   git clone https://github.com/robotont/robotont_gazebo.git
   

2. Build and source the newly added package:

   colcon build --packages-select robotont_gazebo
   source install/setup.bash
   

3. Launch the simulator using the launch file:

   ros2 launch robotont_gazebo gazebo.launch.py
   

Launch file arguments

Name	Description	Options
generation	Specify the generation of robotont model that is to be loaded	2.1, 3 (default)
model	Specify the model that is to be loaded into the world	robotont_gazebo_basic, robotont_gazebo_lidar, robotont_gazebo_nuc (default)
world	Specify world the robot is spawned in	bangbang.sdf, between.sdf, colors.sdf, mapping.sdf, maze.sdf, minimaze.sdf, minimaze_ar.sdf, empty_world.sdf (default)
x, y, z	Specify the robot’s spawn pose	Number, 0 (default)

Tip

For example, loading the generation 3 model in colors.sdf world at pose (-2, 1, 0):

ros2 launch robotont_gazebo gazebo.launch.py world:=colors.sdf x:=-2 y:=1

Worlds

World	Example	Launch Command
minimaze.sdf		ros2 launch robotont_gazebo gazebo.launch.py world:=minimaze.sdf
bangbang.sdf		ros2 launch robotont_gazebo gazebo.launch.py world:=bangbang.sdf
between.sdf		ros2 launch robotont_gazebo gazebo.launch.py world:=between.sdf
colors.sdf		ros2 launch robotont_gazebo gazebo.launch.py world:=colors.sdf
mapping.sdf		ros2 launch robotont_gazebo gazebo.launch.py world:=mapping.sdf
maze.sdf		ros2 launch robotont_gazebo gazebo.launch.py world:=maze.sdf
minimaze_ar.sdf		ros2 launch robotont_gazebo gazebo.launch.py world:=minimaze_ar.sdf

2D Mapping and Localization

Setup

Hint

Before installing any packages from apt, make sure existing packages are up-to-date:

sudo apt update && sudo apt upgrade -y

Hint

ROS packages installed from apt are only available in terminals where the ROS environment has been sourced. To use these packages, you must first source the general ROS 2 environment:

source /opt/ros/jazzy/setup.bash

1. Install Nav2 from apt:

   sudo apt install ros-jazzy-navigation2
   

2. Navigate to your colcon workspace

   cd ~/<your_colcon_workspace>/src
   

3. Clone the depthimage_to_laserscan package

   git clone https://github.com/ros-perception/depthimage_to_laserscan.git --branch ros2
   

4. Build the package:

   colcon build --packages-select depthimage_to_laserscan
   

The demo for 2D slam based navigation is available from this repository.

1. Navigate to your colcon workspace

   cd ~/<your_colcon_workspace>/src
   

2. Clone the 2d_slam package

   git clone https://github.com/robotont-demos/2d_slam.git
   

3. Build the package:

   colcon build --packages-select 2d_slam
   

Running the demo

The demo can be run on a Robotont featuring either a LIDAR or the standard Realsense D435i camera

Robotont with LIDARRobotont with Realsense D435i

1. Spawn LIDAR Robotont in a gazebo world

   ros2 launch robotont_gazebo gazebo.launch.py model:=robotont_gazebo_lidar world:=<world_name>.sdf
   

2. Launch the navigation stack and slam

   ros2 launch 2d_slam nav2_lidar_slam.launch.py
   

3. (Optional) Visualize costmaps and the robot’s model in Rviz2

   ros2 launch 2d_slam rviz2_visualize_costmaps.launch.py
   

Setting 2D navigation goals

Using ROS Navigation to make the robot move autonomously is straightforward. In RViz, you have two main GUI buttons: one to set the robot’s current location (if it doesn’t localize itself accurately at startup), and one to set its navigation goal.

1. To set the initial pose:

   Click on “2D Pose Estimate” in the RViz toolbar, then click and drag the arrow to indicate where the robot is located and which way it is facing.

   

2. To set a navigation goal:

   Click on “2D Goal Pose” in the RViz toolbar, then click and drag the arrow to the desired destination and orientation for the robot.

   

3D mapping

Creates a 3D map of the robot’s surroundings.

Follow the leader

The follow the leader demo shows the capabilities of the Robotont platform to detect and follow the AR Tag.

AR steering

The AR steering demo shows the capabilities of the Robotont platform to detect and follow the AR Tag.

AR maze

The AR maze demo shows the capabilities of the Robotont platform to detect and follow the AR Tag.