Automated Control With Collision Avoidance of Multiple Unmanned air Vehicles

This report is a study of the coordination of multipleunmanned air vehicles (UAV). It begins with the model of a flyingvehicle with four fixed propellers, a so called quadcopter. Themodel describes how movement is related to motor speed, vehiclesize and mass distribution. Secondly we evaluate what sensorsare appropriate to use in an autonomous air vehicle system andwhat outputs they create. The model and the sensor outputs areused to perform automated stability control of a quadcopter, forwhich we propose the use of a PID controller. In the third partof the report we examine possible ways for autonomous vehiclesto perform motion planning. We compare the Potential field, A*and RRT algorithms and choose to implement a program whichsimulates UAVs using a potential field algorithm to navigate. Theprogram is two dimensional and randomly generates a chosennumber of flying units and static obstacles. The potential fieldmethod is not error free, sometimes vehicles get stuck when theirgoal is directly behind an obstacle, but the simulation proves theusability of the algorithm if elaborated with a few minor functionsto avoid specific problem cases. In the last part we discuss someexisting and some future applications of UAVs in a smarter urbanenvironment