Description

Lab5
Overview
The objective of this lab is to get you familiar with the mapping, localization and path planning capabilities of the ROS2 navigation stack. The nal goal is to write a script to make a simulated and real robot autonomously navigate to a series of global waypoints. Unlike previous labs, this is not one in which you will be programming algorithms directly, but rather understanding previously written code/algorithms and tuning the parameters to suit your goals. The o cial documentation for the Nav2 stack is found here,
https://navigation.ros.org/index.html
1 Lab Instructions
1.1 Gazebo Simulation
For this lab, you will be required to leverage Gazebo simulation environment, which can be used for code development and initial testing. A reminder, the tutorial on simulating the Turtlebot in Gazebo and initial modi cations to the simulation environment can be found in Lab 2. In addition to this initial setup, for this lab, we have created a Gazebo environment similar to the one you will nd in the lab to test your navigation code. The les and directions on how to use them are available here,
https://github.gatech.edu/swilson64/7785_Lab5_Gazebo_Files
Note: This maze environment will be identical to the one used for your Final project.
Your team will be expected to perform the lab in simulation and on the robot. To perform this lab in simulation, follow the same steps as in subsection 1.2 and subsection 1.3, but with Gazebo running instead of bringing up the real Turtlebot. Gazebo will subscribe and publish the same messages as the real robot.
1.2 Create a map through teleoperation
Generate a map of your environment using the instructions found at:
http://emanual.robotis.com/docs/en/platform/turtlebot3/slam/
make sure you select the instructions for ROS2 Humble and don’t use the ROS1 Kinetic instructions that the web page defaults to.
Note: If during any of the steps your PC or Turtlebot throws errors of the form,
ERROR: cannot launch node of type [example/example]: example You are missing that <example> package, install it with the command sudo apt-get install ros-humble-example.
You can tab complete to nd the correct name or Google the name of the package to nd the correct instillation command for ROS Humble.
In later stages of the lab, you will have your robot navigate to a prede ned goal. To ensure that everyone uses (approximately) the same global coordinates, start your robot with its wheels on the blue tape marks on the oor, facing in the direction of the arrow. Then drive your robot around to complete the map. You can also save this le wherever you would like in step 9.4.1 by changing the directory and le name after the -f command.
1.3 Localization, Path Planning, and Navigation
To start, use the map you’ve generated to have the robot navigate to a point you specify in the rviz GUI. Instructions found at:
https://emanual.robotis.com/docs/en/platform/turtlebot3/navigation/
make sure you select the instructions for ROS2 Humble and don’t use the ROS1 Kinetic instructions that the web page defaults to.
Note: If you changes the save location of your map les, make sure they are the same as de ned after the map_file:= … command in step 10.1. This navigation is using a avor of particle lter for localization and A*/Djikstra’s for path planning.
After you verify everything is working through the GUI in RViz, you can determine points in your map’s coordinate frame using publish point in the RVIZ GUI and using the following command,
ros2 topic echo /clicked_point
you should notice the topic is publishing the the clicked position. However, the Navigation Stack requires a pose consisting of 3 positional coordinates (x, y, z), and 4 orientation coordinates (x, y, z, w). These four orientation coordinates are a way of representing a rotation called a Quaternion. To publish a navigation goal to the robot rather than using the RVIZ GUI, use the command line argument,
ros2 topic pub /goal_pose geometry_msgs/PoseStamped ’{header: {stamp: {sec: 0,
nanosec: 0}, frame_id: “YOUR_MAP_NAME”}, pose: {position: {x: 3.9, y: -0.85, z: 0.0}, orientation: {x: 0, y: 0, z: 0, w: 1.0}}}’
the message being published here is a PoseStamped geometry message.
https://docs.ros.org/en/diamondback/api/geometry_msgs/html/msg/PoseStamped.html
You will need to use this message type to pass your script’s goal points to the NavStack for this lab.
1.4 Drive to global waypoints
On the day of the lab, 3 random goal points within your map will be chosen for your robot to navigate between. You should be able to put these point into your script through a le or change them easily in your code.
2 Parameters that should be tuned
When using the navigation stack, there are a few parameters you can adjust to get more consistent performance. All of the parameters are found in the turtlebot3/turtlebot3_navigation/param directory, and they’re loaded by the navigation launch le. All you have to do is change the parameters in the .yaml les (you can open these with a text editor), no compiling needed.
Costmap 2D – This provides the environment the robot plans within. The parameters within this section deal with how Dangerous your robot will believe walls are and plan accordingly.
Frequency of Planners – In the controller and cost map parameters, there are frequency parameters. Recall discrete control and Lab 3 where the sampling time impacts performance of controllers. Make sure these frequencies are within the range of your sensors (LIDAR).
For passing waypoints into the Nav Stack from a script, use the ’/goal_pose’ topic which takes a PoseStamped message type.
To determine if the robot has been reached you can use any part of the Nav Stack feedback. One method of doing this is subscribing to the /navigate_to_pose/_action/feedback topic which uses the NavigateToPose_FeedbackMessage message type (https://github.com/rosplanning/navigation2/blob/main/nav2_msgs/action/NavigateToPose.action).
3 Grading
Navigate to 3 waypoints speci ed at grading time in simulation (10% per waypoint) 30%
Navigate to 3 waypoints speci ed at grading time (10% per waypoint) 30%
4 Submission
You have two required submissions for this lab.
1 Your ROS package in a single zip le called TeamName_Lab5.zip uploaded on Canvas under Assignments Lab5.