In today's fast-paced world, the integration of Unmanned Aerial Vehicles (UAVs) has marked a paradigm shift in various industries, particularly in transportation and logistics. Among these cutting-edge technologies, autonomous quadcopters have emerged as frontrunners in revolutionizing the delivery landscape. In this project, I've designed autonomous navigation (flight attitude, position control, & obstacle avoidance) algorithms using ROS, Python, and Gazebo for a 3-D simulated quadcopter capable of autonomously delivering packages in an urban environment. To detect QR codes on delivery packages and identify drop-off locations, I implemented a pyzbar library-based computer vision algorithm. This project was designed for the e-Yantra Robotics Competition hosted by IIT Bombay and sponsored by the Ministry of Education of India.