The last decade has seen an increase in research of autonomous vehicles. This research tries to tackle autonomy in Unmanned Aerial Vehicles (UAV) by specifically designing decentralized controllers for platooning. An extensive review of closely related research inspires the use of state-of-the-art tools like AirSim and RotorS that have been tested for their viability for this research. A fusion of sensors trained using Deep RL, a Reinforcement Learning technique is chosen to guide drones in impact regions where traditional sensors have limited ability. The goal of this research is to make robust controllers for drone swarms for search and rescue.