Development Of Autonomous Drone For Multipurpose Functions

Autonomous drones can carry out functions such as emergency aid delivery, parcel delivery or inspection works with the help of global positioning system (GPS) location tracker, along with sensors for object avoidance. This thesis provides understanding of UAV and the mechanisms that work together to enable its flight, elaborates the different functions that the autonomous drone is designed to carry out, performs flight data analysis from flash logs on Mission Planner (MP) and Google Earth, and discusses how different objectives – including building the UAV model by considering suitable hardware, object avoidance using HC-SR04 or Maxbotix ultrasonic sensor with Arduino IDE, real-time GPS tracking of drone with Ardupilot (APM) software – are achieved with the current state of technology. The drone uses Raspberry Pi (RPi3) as the processor and a stackable flight controller, Navio2 by Emlid to control its flight. Navio2 is a well-documented, latest developed flight controller (FC) by Emlid, with an array of built-in sensors to assist through different autopilot missions. Advanced Inertial Measurement Unit (IMU) feeds real time flight data to the processor as well as the Ground Control Station (GCS). Global Navigational Satellite System (GNSS) receiver accepts satellites’ signal to pinpoint location of UAV, assist the UAV’s flight over waypoints (WP) in auto modes, and override inaccurate flight parameters through Extended Kalman Filter (EKF). With an external 915 MHz radio telemetry in place flight data can be monitored from GCS even without the need of a Local Area Network (LAN) connection. The drone utilises a 12-channel AT10-II RCtransmitter and receiver pair by RadioLink Electronics to enable manual or semi-autonomous control and initiation operations of autonomous mode. A reliability study of the drone is carried out based on failure tree and criticality analysis. The drone is successfully set on mission on GPS tracking and path planning in autonomous mode and is able to respond to obstacles in the object avoidance mode with suitable pitch and roll values based on detected distances