Unmanned aerial vehicles (UAVs) are used in different environmental applications like military and civilian domains. For those domains, UAVs need to adopt different conditions on basis of, inspection, reconnaissance, remote sensing, target achievement, border patrol, infrastructure monitoring, aerial imaging, industrial inspection, and emergency medical aid. Autonomous Control of Unmanned Aerial Vehicles must able to make a resolution and respond to events without direct interference by humans. To make UAVs completely autonomous, still it needs many technological and algorithmic developments. For that, UAVs will need certain improvements in their recognizing of obstacles and successive avoidance.
Autonomous Control of Unmanned Aerial Vehicles deals with self-analyzing systems and GPS systems in the existence of artificial intelligence to make decisions to control. There are a certain fundamental featurescommon to all autonomous vehicles which include the recognition abilities and discern the environment, analyzing the sensed information, transmitting, planning and decisions making, as well as acting using control algorithms and actuators. The path planning algorithm helps to define the path and artificial intelligence provides decisions based on the present environment. The control system is trying out in a real-time experiment and,employing simulations exhibits refinements in the hardness of a quadrotor subject to a slung load.Certain experiments are needed to carry out with multiple sets of real times scenarios that are described and signify the efficacy of automation. Thusby this process, the Autonomous Control of Unmanned Aerial Vehicles has experimented.
ALGORITHM AND ITS FUNCTIONS: