auto_nav

Performing autonomous maze exploration using wall following algorithm. Automatically detect NFC for loading ping pong ball. Autonomous aiming and firing at hot target.

What does the code have

Provided that your robot has the similar design like our robot, this repository includes all the necessary code to perform an autonomous exploration of a 2D maze, detect NFC tag to stop and fire ping pong ball at hot targets. For details of the design of our robot, you can go to our Documentation file to read about the details of our robot.

• self_exploration.py file is the code for our exploration algorithm. The code structure bases on a Finite State Machine as shown below:

• actuation.py file contains the code for our sensors on the Turtlebot3. The code continously read NFC, IR sensor and a button at a rate of 10Hz and reports the value to the exploration program through the 3 topics /hot_target, /nfc and /button.

• base_code folder contains all the original files that comes with the initial fork from shihchengyen's r2auto_nav repository.

• test_code folder contains all the python scripts to test sensor components on the Turtlebot3. Refer to the Documentation for details.

• Documentation file refers to the detail of our design including mechanical and electrical designs.

Configuration for your own environment

self_exploration.py

• Under #some variable to tune your bot, you can change wall_following_dir to decide which side of the wall your robot will follow. Only the value of 1: Right Wall Following and -1: Left Wall Following are allowed.
• Inside the attributes of the class, you can adjust self.fsm to decide which state you want to start with. Please refer to the diagram above.

actuation.py

Under constants, you can change :

• heat_threshold which determines the target detection temperature threshold and firing_threshold which determines the firing temperature threshold to fit your needs.

How to install and run your code

In your laptop:

• Create a ROS2 package and clone this repository into that package using git clone [email protected]:nguyen2001ag/r2autonav.git. Make sure to edit the setup.py file to run the code.
• Build the package.

In the RPi on the TurtleBot:

• Create a ROS2 package and copy actuation.py file into that package. Make sure setup.py is edited to include the code.
• Build the package.

Running Instructions:

• ssh into the Raspberry Pi on the Turtlebot.
• Start the bringup from the RPi on the TurtleBot: roslaunch turtlebot3_bringup turtlebot3_robot.launch
• Start rslam from your laptop: ros2 launch turtlebot3_cartographer cartographer.launch.py
• Start the actuation code from the RPi on the TurtleBot: ros2 run <package_name> <entry_point_specified_in_the_setup.py>
• Start the wall following code from your laptop: ros2 run <package_name> self_exploration