Autonomous UAV with Human Detection

Abstract

The use of Unmanned Aerial Vehicles (UAV) is increasing tremendously and with it the need for autonomous flight. In this paper, it is discussed how an autonomous UAV is built with the help of a cascaded Proportional Integral Derivative controller and Simultaneous Localization and Mapping (SLAM). The simplistic design and easily available components make a light weight quadcopter style UAV. A Human detection neural network is also added to the UAV which can be used for many applications such as aerial photography, search and rescue, defense. In previous papers the UAVs processed data on board which in turn caused the UAV to use huge amounts of memory and processing power, thereby increasing the power consumption and cost. Whereas the UAV system proposed in this paper transmits raw data to the main control station for processing in turn reducing the on board processing and avoiding the use of costly controllers.