Visual Tracking and Control of a Quadrocopter

The main goal of this master thesis project was to take a manually controlled consumer quality quadrocopter and build the foundations which allows it to be autonomously controlled. This was achieved by introducing a exterior frame of reference through the use of a webcam coupled with image analysis algorithms. The position and rotation of the quadrocopter was identified, and several control structures were implemented and tested, which allowed the quadrocopter to be commanded to move to positions in space. Both the onboard ultrasound sensor, and an altitude estimation through image analysis were used to control the altitude of the quadrocopter. Position control in x, y and orientation (yaw rotation) completely relied on data extracted and analysed from the video stream. Control of velocity along a predefined trajectory was also successfully implemented, which enables future development of an obstacle avoiding path planner. Lastly, the master thesis also covers work carried out at ABB’s Strategic R&D department for oil, gas and petrochemicals i Oslo, Norway. Here the focus was on using a quadrocopter to track and follow the motion of an industrial robot by analysing the video stream of the onboard camera

Modeling, identification and navigation of autonomous air vehicles

The main interest of this work is autonomous navigation of autonomous air vehicles, specifically quadrotor helicopters (quadrocopters), and the focus is on convergence to a target destination with collision avoidance. The controller computes a collision-free path leading to the target position and is based on a navigation function approach and waypoints are followed exploiting PID controller

ROSSi a graphical programming interface for ROS 2

The Robot Operating System (ROS) offers developers a large number of ready-made packages for developing robot programs. The multitude of packages and the different interfaces or adapters is also the reason why ROS projects often tend to become confusing. Concepts of model-driven software development using a domain-specific modeling language could counteract this and at the same time speed up the development process of such projects. This is investigated in this paper by transferring the core concepts from ROS 2 into a graphical programming interface. Elements of established graphical programming tools are compared and approaches from modeling languages such as UML are used to create a novel approach for graphical development of ROS projects. The resulting interface is evaluated through the development of a project built on ROS, and the approach shows promise towards facilitating work with the Robot Operating System

Autonomous Quadrocopter for Search, Count and Localization of Objects

This chapter describes and evaluates the design and implementation of a new fully autonomous quadrocopter, which is capable of self‐reliant search, count and localization of a predefined object on the ground inside a room

Computer Vision Based Object Detection and Tracking in Micro Aerial Vehicles

­­­­The ultimate goal of Computer Vision is to instruct a computer to understand and interpret visual signals and images in real time and to instruct a computer to react to the environment around them. In this work, we describe a system that allows a micro aerial vehicle (MAV), equipped with an onboard camera, to detect and track a moving target object. In an alternative implementation, the MAV instead searches the environment for the target object and flies to it. Due to the limited capability of the drone’s integrated processor, image processing is performed by a ground-based computer that also determines the necessary flight corrections and communicates them to the vehicle. The complete system, comprised of the MAV, off-board computer, and software, operates autonomously, a necessary condition for many of the applications for which such systems may be useful

Design, Implementation, and Performance Study of an Open Source Eye-Control System to Pilot a Parrot AR.Drone Quadrocopter

Natural user interface is a fairly new concept in the field of human-computer interaction. It is the idea of using every day natural human behaviors and actions to control a device. An example of a natural user interface is touch control technology in smartphones, tablets, and new laptops. The interaction is more direct when compared to artificial input devices like a keyboard and mouse. Though natural user interface devices might not perform as well as standard input devices for certain applications, for other applications they are now the de facto standard. A new user interface that is poised to be the next natural user interface in human-computer interaction is eye-control, or the ability to control an interface with just the user’s eyes using technology that has been around for a long time called eye trackers. The problem for much of the existence of eye trackers is the cost. Most modern commercial eye trackers cost anywhere between $10,000 and$40,000, and that is too expensive for regular consumers to buy and use. In this paper, we build a low cost system for eye-control using an open source program called ITU Gaze Tracker. In the process, we developed an interface which allows a user to pilot a Parrot AR.Drone quadrocopter using just their gaze. In this explorative study, we explore the performance of this eye-control system to keyboard control in the operation of an AR.Drone around an obstacle course. We collected certain performance metrics like lap completion time