The 'Elevator' Problem: S/Ue

This repository was developed for NUS AY23/24 S2 EG2310. It includes navigation & communications code written for a TurtleBot 3 operating on ROS2, called S/Ue, because this module gave us so much emotional trauma that S/U-ing is the only logical choice.

To anyone taking this module, good luck.

Description

The mission requires developing an integrated robot system which can autonomously navigate through a randomised maze, up until an 'elevator lobby' right after the exit.

In the lobby, the robot is to send an HTTP request to a web server, which will trigger a random 1 of 2 doors top open.The server will also send a JSON response to the robot ID-ing the correct door.

The robot will then proceed to the door and locate a bucked in a randomised location on the other side. From there, it will release 5 ping pong balls into the bucket.

Finally, the robot will return to the maze develop a full map of the area using SLAM.

NOTE: Use of this repository requires the phsyical assembly of S/Ue. Installation instructions below are specific for the Remote PC. Full hardware & technical documentation can be found in the documentation folder.

Getting Started

Software Dependencies

• Ubuntu 20.04

Installing

Install ROS2 Foxy on Remote PC

wget https://raw.githubusercontent.com/ROBOTIS-GIT/robotis_tools/master/install_ros2_foxy.sh
sudo chmod 755 ./install_ros2_foxy.sh
bash ./install_ros2_foxy.sh

Install Dependent ROS2 packages

Install Gazebo

sudo apt-get install ros-foxy-gazebo-*

Install Cartographer

sudo apt install ros-foxy-cartographer
sudo apt install ros-foxy-cartographer-ros

Install Navigation2

sudo apt install ros-foxy-navigation2
sudo apt install ros-foxy-nav2-bringup

Install Slam Toolbox

sudo apt install ros-foxy-slam-toolbox

Install TurtleBot3 Packages

source ~/.bashrc
sudo apt install ros-foxy-dynamixel-sdk
sudo apt install ros-foxy-turtlebot3-msgs
sudo apt install ros-foxy-turtlebot3

Configure Environment for ROS2 Develoopment

echo 'export ROS_DOMAIN_ID=30 #TURTLEBOT3' >> ~/.bashrc
echo 'export TURTLEBOT3_MODEL=burger' >> ~/.bashrc
source ~/.bashrc

Create Aliases

For ease of use, we have created the following aliases which we have added to the ~/.bashrc of our Remote PC and RPi4. We have listed them below.

Note: For our mission we had setup an AWS server which allows us to fetch the RPi4's IP-address whenever sshrp was called.

Remote PC Alias	Command
sshrp	ssh ubuntu@<RPi4 IP-address>
toolbox	ros2 launch slam_toolbox online_async_launch.py
rvm	cd ~/.rviz2 && rviz --display-config mission.rviz
ctl	cd ~/colcon_ws && colcon build --packages-select auto_nav && cd ~/colcon_ws/src/auto_nav/auto_nav && ros2 run auto_nav control
exp	cd ~/colcon_ws && colcon build --packages-select auto_nav && cd ~/colcon_ws/src/auto_nav/auto_nav && ros2 run auto_nav explore
rteleop	ros2 run turtlebot3_teleop teleop_keyboard

RPi4 Alias	Command
rosbu	ros2 launch turtlebot3_bringup robot.launch.py
line	cd ~/turtlebot3_ws/src && colcon build --packages-select r2auto_nav && source install/setup.bash && ros2 run r2auto_nav l

Setting Up RViz Environment

Run Slam Toolbox

toolbox

Open RViz

rviz

Add the following Nodes:

• Map
• LaserScan
• Marker Array
• Interactive Markers

File>Save Config and save to the default directory, ~/.rviz, named as mission.rviz (So that this configuration launches upon calling rvm)

Executing program

Place S/Ue on the starting line.

Terminal 1: Bringup the TurtleBot

sshrp
rosbu

Terminal 2: Launch slam

toolbox

Terminal 3: Launch RViz

rvm

Terminal 4: Run control.py or explore.py,

ctl
# OR
exp

Terminal 5: Run lineFollower.py

sshrp
cd turtlebot3_ws/src/r2auto_nav/r2auto_nav/
python3 lineFollower.py

S/Ue should then proceed to execute the mission.

Troubleshooting

• To test S/Ue's movement independently, use rteleop to manually control movement.
• To test payload execution, run python3 payload.py.

Authors

Contributors names and contact info

Namit Deb [email protected]

Wong Weng Hong [email protected]

Anitej Datta [email protected]

Vishwanath Annanya [email protected]

Anupama Sriram [email protected]

Acknowledgments

The navigation algorithm developed in control.py was developed by Abdulkadir TÜRE. Find his repo here.

The algorithm developed in explore.py implements elements of control.py and r2files/r2_auto.nav.py developed by Dr. Shih-Cheng Yen.