Master's thesis about autonomous navigation of a drone in indoor environments carried out to obtain the degree of Master of Science in Computer Science Engineering (University of Liège, academic year 2020-2021).

Autonomous drone simulation with LQR controller, trajectory planning, obstacle avoidance features in ROS2 and Python

Autonomous drone using detected ball to command the direction of the drone

Simulation ROS package for an autonomous delivery drone

A smart autonomous drone with Object Tracking and Object Detection capabilities

Autonomous control of multirotor with PX4 and Ardupilot using ROS (Robot Operating System)

Precision Landing implmented in AirSim with python and openCV, window identification neural network in dron using tensorflow

A GUI-based drone control application written in Python using the Tkinter library. This application allows users to control a drone, manage its waypoints, and visualize its position on a grid. The application is designed to work seamlessly with the UGCS SDK.

Fire detection & precision landing drones with DroneKit, YOLOv4, OpenCV and ROS

Monitor endangered wildlife and assess potential threats using autonomous drones

A modified version of "Dronet: Learning to Fly by Driving", for the specific application of Drone Racing.

This is a Autonomous drone navigation system that takes x,y,z coordinates as input and using a robust control system,smoothly navigates to the point.

Simulator of a squad of drone doing a Q-Learning algorithm to maximize packet delivered to depot, for the HW1 on University Course AN