This repository aims to maintain the research made in my master's thesis. The title of the project is "Position and Attitude Estimation of a Quadrotor Using Computer Vision", where the main task is to accomplish indoor navigation in a GPS-denied environment using computer vision techniques. The state estimation was made using Error State Kalman Filter [1] and for the quadrotor's control, it was implemented a cascade PID. The simulations are available in Video Simulation.

Clone this repository and follow the instructions:

1 - Build a Docker image:

~$ docker build . -t quad_ufabc:latest

2 - Run shell script to create the Docker container:

~$ sudo bash start_container.bash

3 - Execute the commands located on Running application section of this repository.

The ROS version used in this work is Noetic. The official installation guide can be accesed on:ROS Noetic Installation. It is reccommended in 1.4 Installation topic, the choice of the option Desktop-Full Install, because it already install all the dependencies, including the Gazebo simulator.

After ROS/Gazebo installation, it is necessary create a workspace. Open the terminal on Ubuntu, and follow the instrunctions:

• Install some dependencies of ROS:

~$ sudo apt-get install ros-noetic-ros-control ros-noetic-ros-controllers -y

• Create a work directory:

~$ mkdir /path/to/work/directory

• On the created directory, create another folder called src and initialize the workspace:

~$ mkdir /path/to/work/directory/src
~$ cd /path/to/work/directory/src
~$ source /opt/ros/noetic/setup.bash
~$ catkin_init_workspace 

• Compile workspace:

~$ cd ..
~$ catkin_make

• Configure the .bashrc:

~$ echo "source /path/to/work/directory/devel/setup.bash" >> ~/.bashrc
~$ source ~/.bashrc

• Clone this repository, copy and paste the src folder into the work directory.

• Create a virtual environment (in this case, we will use venv from Python, but feel free to use another one):

~$ python3 -m venv venv
~$ source venv/bin/activate

• On cloned repository, run the python dependencies installation using pip:

~$ pip install -r requirements.txt

Initialize Gazebo:

~$ roslaunch quad_ufabc quad.launch

Run simulation

~$ rosrun quad_ufabc main.py

[1] SOLÀ, J. Quaternion kinematics for the error-state kalman filter. 2017.