Development of Unmanned Aerial Vehicle (Quadcopter)With Real-Time Object Tracking

Abstract

In the previous decade, Unmanned Aerial Vehicles (UAVs) have turned into a subject of enthusiasm for some exploration associations. UAVs are discovering applications in different regions going from military applications to activity reconnaissance. This thesis is an overview of a particular sort of UAV called quadrotor or quadcopter. Scientists are often picking quadrotors for their exploration because a quadrotor can precisely and productively perform assignments that future of high hazard for a human pilot to perform. This thesis includes the dynamic models of a quadrotor and model-autonomous control systems. It also explains the complete description of developed quadcopter used for surveillance purpose with real-time object detection. In the present time, the focus has moved to outlining autonomous quadrotors. Ultimately, it examines the potential applications of quadrotors and their part in multi-operators frameworks. The Unmanned aerial vehicle (Quadcopter) has been developed that could be used for search and surveillance purpose. This project comprised of both hardware and software part. The hardware part comprised of the development of unmanned aerial vehicle (Quadcopter). The main components that were used in this project are KK2 flight controller board, outrunner brushless DC motor, Electronic Speed Controllers (ESC), GPS (Global Positioning System) receiver, video transmitter and receiver, HD (High Definition) camera, RC (Radio Controlled) transmitter and receiver. Software part comprised of real-time object detection and tracking algorithm for detecting and tracking of human beings that were done with the help of Matlab software. After achieving the stable flight, the camera installed on the quadcopter would transmit a video signal to the receiver placed on the ground station. Video signal from the receiver would then be transferred to Matlab software for further processing or for tracking human beings using real-time object detection and tracking algorithm