The main goal of the following project was developing a trajectory control algorithm for a quadcopter in order to move on a grid. Another objective was designing a control system for linear speed in order to stabilize the ight. Moreover, the important part was implementing the algorithms being in charge of optimal path planning. The nal application of the project is implementing a program allowing a drone to perform a ight from node A to node B, with a minimum cost of paths visited. For this purpose, a network of nodes and paths has been created that simulates for example an application in a warehouse. The project uses image processing tools in order to follow the line (and detect intersections). The aircraft used for experiments was Parrot AR Drone 2.0. The drone communicates with the PC via a wireless Wi-Fi network. In order to obtain the connection, two appropriate operating systems were used: Robot Operating System ROS and Linux. All functions controlling the Drone have been implemented using the MATLAB environment and control simulations have been conducted in Simulink.

Incoming