TurtleBot Data Acquisition and Visualization System

This robust project is designed to capture, store, and visually represent telemetry data from a TurtleBot using the Robot Operating System (ROS). The framework employs a custom-built ROS node for real-time data acquisition, which is then stored in the high-performance InfluxDB time-series database.

One of the unique features of this system is the seamless data transfer mechanism from InfluxDB to a MySQL database, facilitated by a specific task built using the powerful Django web framework. This process allows for enhanced data manipulation and the ability to leverage SQL-based analysis on collected telemetry data.

To provide users with a comprehensive visual understanding of the TurtleBot's operations, this project utilizes Grafana, a multi-platform open-source analytics and interactive visualization web application. Data is presented through custom-built Grafana dashboards, providing users with insights into the TurtleBot's operations at a glance.

Additionally, a custom Django webpage offers another layer of data visualization, enabling users to interact with and analyze the TurtleBot data from various perspectives.

This project serves as a comprehensive solution for gathering, storing, and visualizing TurtleBot telemetry, effectively catering to research, testing, and monitoring purposes. It stands as a testament to the power of integrating multiple open-source tools to deliver a highly functional and flexible telemetry data management platform.

Installation

Prerequisites

Install ROS. Refer to this documentation for a comprehensive guide on how to install ROS and calibrate and control TurtleBot.
Install MySQL. Follow the steps in this DigitalOcean tutorial to install MySQL on Ubuntu 20.04. After installation, create a new database named rosdb using the following SQL command:

  CREATE DATABASE rosdb;

Install Grafana using this documentation.
Setup Grafana to connect with InfluxDB using this guide.

Clone the repository

Clone the repository into your catkin src directory with the command:

cd ~/catkin_ws/src
git clone https://github.com/abujarad21/CPS_Monitoring.git

Build the project

Navigate back to the root of your catkin workspace and build the project using catkin_make:

cd ~/catkin_ws
catkin_make

Set up the Django project

Navigate to the directory containing the Django project (it should be within the cloned repository).
Install the necessary Python packages by running:

cd ~/catkin_ws/src/CPS_Monitoring/djangoproject/
pip install -r requirements.txt

Run the following commands for database migrations:

python manage.py makemigrations
python manage.py migrate

Note: The Django project will not be built using catkin_make, as it is not a ROS node.

Usage

Start the ROS core by running the command roscore in the host PC.
On the TurtleBot, run the following commands each one in one robot resberrypi:

ROS_NAMESPACE=tb3_0 roslaunch turtlebot3_bringup turtlebot3_robot.launch set_base_frame:=tb3_0/base_footprint set_odom_frame:=tb3_0/odom set_map_frame:=tb3_0/map

ROS_NAMESPACE=tb3_1 roslaunch turtlebot3_bringup turtlebot3_robot.launch set_base_frame:=tb3_1/base_footprint set_odom_frame:=tb3_1/odom set_map_frame:=tb3_1/map

On the host PC, run the following commands each one in one tab:

ROS_NAMESPACE=tb3_0 roslaunch turtlebot3_bringup turtlebot3_remote.launch multi_robot_name:=tb3_0

ROS_NAMESPACE=tb3_1 roslaunch turtlebot3_bringup turtlebot3_remote.launch multi_robot_name:=tb3_1

To control the TurtleBot, run the following commands each one in one tab:

ROS_NAMESPACE=tb3_0 rosrun turtlebot3_teleop turtlebot3_teleop_key

ROS_NAMESPACE=tb3_1 rosrun turtlebot3_teleop turtlebot3_teleop_key

Run the influxdb_monitoring node:

rosrun influxdb_monitoring msgs_to_influxdb_basic.py

Inside the Django project directory, start the Django task to transfer data from InfluxDB to MySQL each in one tab:

cd ~/catkin_ws/src/CPS_Monitoring/djangoproject/
celery -A influxdb2mysqldb worker --loglevel=info

cd ~/catkin_ws/src/CPS_Monitoring/djangoproject/
celery -A influxdb2mysqldb beat --loglevel=info

Run the Django server on port 8000:

cd ~/catkin_ws/src/CPS_Monitoring/djangoproject/
python manage.py runserver 8000

Contributing

If you would like to contribute, please fork the repository and use a feature branch. Pull requests are warmly welcome.

License

The project is licensed under the MIT license.

Contact

If you have any questions, please feel free to contact me at Abujarad73@gmail.com.