ROS Navigation

Learning Objectives

In this ROS example, We will

• Demonstrate Omniverse Isaac Sim integrated with the ROS Navigation stack.

• Use the Occupancy Map Generator.

Getting Started

Prerequisite

• The ROS Navigation stack is required to run this sample. Install the ROS Navigation stack:

  sudo apt-get install ros-$ROS_DISTRO-navigation
  

• This tutorial requires carter_2dnav, carter_description, and isaac_ros_navigation_goal. The packages are located under the directory <noetic_ws>/src/navigation/. They contain the required launch file, navigation parameters, and robot model. Complete ROS and ROS 2 Installation, make sure ROS environment is setup correctly and those packages are inside your ROS_PACKAGE_PATH.

• ROS bridge is enabled and roscore is running before running Omniverse Isaac Sim.

• OPTIONAL: Explore the inner workings of RTX Lidar sensors by learning How They work, the RTX Lidar Nodes that use them, and how to get RTX Lidar Synthetic Data.

The ROS Navigation Setup

This block diagram shows the ROS messages required for the ROS Navigation stack.

As described above, the following topics and message types being published to the ROS Navigation stack in this scenario are:

ROS Topic	ROS Message Type
/tf	tf2_msgs/TFMessage
/odom	nav_msgs/Odometry
/map	nav_msgs/OccupancyGrid
/scan	sensor_msgs/LaserScan

Carter_ROS OmniGraph Nodes

Go to Isaac Examples -> ROS -> Navigation to load the warehouse scenario.

1. Open the main ActionGraph by expanding Carter_ROS. Right click on ActionGraph and press Open Graph. The following ROS OmniGraph nodes are setup to do the following:

   Omnigraph Node	Function
   ros1_subscribe_twist	Subscribes to the /cmd_vel topic and triggers the differential and articulation controllers to the move the robot
   ros1_publish_odometry	Publishes odometry received from the isaac_compute_odometry_node
   ros1_publish_raw_transform_tree	Publishes the transform between the odom frame and base_link frame
   ros1_publish_transform_tree	Publishes the static transform between the base_link frame and chassis_link frame. Keep in mind that since the target prim is set as Carter_ROS, the entire transform tree of the Carter robot (with chassis_link as root) will be published as children of the base_link frame
   ros1_publish_transform_tree_01	Publishes the static transform between the chassis_link frame and carter_lidar frame
   ros1_publish_laser_scan	Publishes the 2D LaserScan received from the isaac_read_lidar_beams_node

2. Open the ROS_Cameras graph by expanding Carter_ROS. Right click on ROS_Cameras and press Open Graph. The following ROS Camera OmniGraph nodes are setup to do the following:

   Omnigraph Node	Function
   ros1_create_camera_left_info	Auto-generates the CameraInfo publisher for the /camera_info_left topic. It automatically publishes since the enable_camera_left branch node is enabled by default
   ros1_create_camera_left_rgb	Auto-generates the RGB Image publisher for the /rgb_left topic. It automatically publishes since the enable_camera_left and enable_camera_left_rgb branch nodes are enabled by default
   ros1_create_camera_left_depth	Auto-generates the Depth (32FC1) Image publisher for the /depth_left topic. To start publishing, ensure enable_camera_left and enable_camera_left_depth branch nodes are enabled
   ros1_create_camera_right_info	Auto-generates the CameraInfo publisher for the /camera_info_right topic. To start publishing, ensure the enable_camera_right branch node is enabled
   ros1_create_camera_right_rgb	Auto-generates the RGB Image publisher for the /rgb_right topic. To start publishing, ensure enable_camera_right is enabled. The enable_camera_right_rgb branch node is already enabled by default
   ros1_create_camera_right_depth	Auto-generates the Depth (32FC1) Image publisher for the /depth_right topic. To start publishing, ensure enable_camera_right and enable_camera_right_depth branch nodes are enabled

3. Finally, to ensure all external ROS nodes reference simulation time, a ROS_Clock graph is added which contains a ros1_publish_clock node responsible for publishing the simulation time to the /clock topic.

Generate Occupancy Map

In this scenario we will use an occupancy map. To generate a map there are 2 options:

1. Using the Occupancy Map Generator extension within Omniverse Isaac Sim (Recommended)

2. Using the slam_gmapping ROS package

Using the Occupancy Map Generator extension (Recommended):

To learn more about the Occupancy Map Generator extension click here.

1. Go to Isaac Examples -> ROS -> Navigation to load the warehouse scenario.

2. At the upper left corner of the viewport, click on Camera. Select Top from the dropdown menu.

3. Go to Isaac Utils -> Occupancy Map.

4. In the Occupancy Map extension, ensure the Origin is set to X: 0.0, Y: 0.0, Z: 0.0. For the lower bound, set Z: 0.1. For the Upper Bound, set Z: 0.62. Keep in mind, the upper bound Z distance has been set to 0.62 meters to match the vertical distance of the Lidar onboard Carter with respect to the ground.

5. Select the warehouse_with_forklifts prim in the stage. In the Occupancy Map extension, click on BOUND SELECTION. The bounds of the occupancy map should be updated to incorporate the selected warehouse_with_forklifts prim. The map parameters should now look similar to the following:

   

   A perimeter will be generated and it should resemble this Top View:

   

6. Remove the Carter_ROS prim from the stage.

7. Once the setup is complete, click on CALCULATE followed by VISUALIZE IMAGE. A Visualization popup will appear.

8. For Rotate Image, select 180 degrees and for Coordinate Type select ROS Occupancy Map Parameters File (YAML). Click RE-GENERATE IMAGE. The ROS camera and Isaac Sim camera have different coordinates.

9. Occupancy map parameters formatted to YAML will appear in the field below. Copy the full text.

10. Create a YAML file for the occupancy map parameters called carter_warehouse_navigation.yaml and place it in the map directory which is located in the sample carter_2dnav ROS package (carter_2dnav/map/carter_warehouse_navigation.yaml).

11. Insert the previously copied text in the carter_warehouse_navigation.yaml file.

12. Back in the visualization tab in Omniverse Isaac Sim, click Save Image. Name the image as carter_warehouse_navigation.png and choose to save in the same directory as the map parameters file.

    The final saved image will look like the following:

    

An occupancy map is now ready to be used with ROS Navigation!

Using the slam_gmapping ROS package:

• Install the slam_gmapping ROS package, run the command below:

  sudo apt-get install ros-$ROS_DISTRO-slam-gmapping
  

• Install the teleop_twist_keyboard ROS package:

  sudo apt-get install ros-$ROS_DISTRO-teleop-twist-keyboard
  

1. Go to Isaac Examples -> ROS -> Navigation to load the warehouse scenario. Press Play to begin simulation.

2. Run the carter_slam_gmapping launch file. This launch file is responsible for spinning up RViz and the pointcloud_to_laserscan node to flatten the Point Cloud from Carter to a laserscan.

   roslaunch carter_2dnav carter_slam_gmapping.launch
   

3. Follow the tutorial: http://wiki.ros.org/slam_gmapping/Tutorials/MappingFromLoggedData

   Note

   Since a rosbag is not available, substitute the rosbag command in the tutorial with the following command: rosrun teleop_twist_keyboard teleop_twist_keyboard.py. This will start the teleop_twist_keyboard ROS node and enable you to use your keyboard to manually drive the robot around the warehouse to simultaneously generate a map.

4. Press Stop to terminate the simulation.

Running ROS Navigation

1. Go to Isaac Examples -> ROS -> Navigation to load the warehouse scenario.

2. Click on Play to begin simulation.

3. In a new terminal, run the ROS launch file to begin ROS Navigation.

   roslaunch carter_2dnav carter_navigation.launch
   

   RViz will open and begin loading the urdf model of the robot, the global occupancy map, as well as the local costmap which will be overlaid on top.

4. To verify that all of the transforms are broadcasting, run the following command in a new terminal to visualize the ROS TF frame tree:

   rosrun rqt_tf_tree rqt_tf_tree
   

   The generated graph should look similar to the one shown below.

   

5. Since the position of the robot is defined in carter_navigation.launch, the robot should already be properly localized. If required, the 2D Pose Estimate button can be used to re-set the position of the robot.

6. Click on the 2D Nav Goal button and then click and drag at the desired location point in the map. The ROS Navigation stack will now generate a trajectory and the robot will start moving towards its destination!

Sending Goals Programmatically

The isaac_ros_navigation_goal ROS package can be used to set goal poses for the robot using a python node. It is able to randomly generate and send goal poses to the navigation stack. It is also able to send user-defined goal poses if needed.

1. Make any changes to the parameters defined in the launch file found under isaac_ros_navigation_goal/launch as required. The parameters are described below:

   • goal_generator_type: Type of the goal generator. Use RandomGoalGenerator to randomly generate goals or use GoalReader for sending user-defined goals in a specific order.

   • map_yaml_path: The path to the occupancy map parameters yaml file. Example file is present at isaac_ros_navigation_goal/assets/carter_warehouse_navigation.yaml. The map image is being used to identify the obstacles in the vicinity of a generated pose. Required if goal generator type is set as RandomGoalGenerator.

   • iteration_count: Number of times goal is to be set.

   • action_server_name: Name of the action server.

   • obstacle_search_distance_in_meters: Distance in meters in which there should not be any obstacle of a generated pose.

   • goal_text_file_path: The path to the text file which contains user-defined static goals. Each line in the file has a single goal pose in the following format: pose.x pose.y orientation.x orientation.y orientation.z orientation.w. Sample file is present at: isaac_ros_navigation_goal/assets/goals.txt. Required if goal generator type is set as GoalReader.

   • initial_pose: If initial_pose is set, it will be published to /initialpose topic and goal poses will be sent to action server after that. Format is [pose.x, pose.y, pose.z, orientation.x, orientation.y, orientation.z, orientation.w].

2. To run the launch file, use the following command:

   roslaunch isaac_ros_navigation_goal isaac_ros_navigation_goal.launch
   

Note

The package will stop processing (setting goals) once any of the below conditions are met:

1. Number of goals published till now >= iteration_count.

2. If GoalReader is being used then if all the goals from file are published, or if condition (1) is true.

3. A goal is rejected by the action server.

4. In case of RandomGoalGenerator, if a goal was not generated even after running the maximum number of iterations, which is rare but could happen in very dense maps.

To learn more about programmatically sending navigation goals to multiple robots simultaneously see Sending Goals Programmatically for Multiple Robots.

Troubleshooting

If you are noticing performance related issues with the ROS Navigation stack or errors such as:

Could not transform the global plan to the frame of the control

• Consider increasing the transform_tolerance parameter for the local and global occupancy maps found in local_costmap_params.yaml and global_costmap_params.yaml.

Summary

In this tutorial, we covered

1. Occupancy map

2. Running Isaac Sim with ROS navigation stack.

3. Running the Isaac ROS Navigation Goal package to send nav goals programmatically.

Next Steps

Continue on to the next tutorial in our ROS Tutorials series, Multiple Robot ROS Navigation to move multiple navigating robots.

Further Learning

• To learn more about ROS Navigation.

• More about Mapping.