Airborne collision scenario flight tests: impact of angle measurement errors on reactive vision-based avoidance control

The future emergence of many types of airborne vehicles and unpiloted aircraft in the national airspace means collision avoidance is of primary concern in an uncooperative airspace environment. The ability to replicate a pilot’s see and avoid capability using cameras coupled with vision based avoidance control is an important part of an overall collision avoidance strategy. But unfortunately without range collision avoidance has no direct way to guarantee a level of safety. Collision scenario flight tests with two aircraft and a monocular camera threat detection and tracking system were used to study the accuracy of image-derived angle measurements. The effect of image-derived angle errors on reactive vision-based avoidance performance was then studied by simulation. The results show that whilst large angle measurement errors can significantly affect minimum ranging characteristics across a variety of initial conditions and closing speeds, the minimum range is always bounded and a collision never occurs

Effects of introducing an interactive teaching and learning activity (TLA) in the engineering classroom

This research study examines qualitatively and quantitatively the influence of introducing an activity in the traditional engineering classroom. It studies instances of active learning and its relationship with the student learning outcomes. The primary purpose of this study was to compare the learning outcomes of students who were involved in an active TLA with those students who were not, instead they learned under traditional teaching and studying approaches. I present the argument that the introduction of a TLA in class stimulates student engagement bringing enormous benefits to student learning. The outcomes of this study were measured using qualitative and quantitative data to evaluate the levels of student engagement, achievement and satisfaction in the terms of Intended Learning Outcomes (ILOs). Results indicate that students held positive attitude towards the activities in class and also, that a positive link between TLA, learning approach and learning outcome exist. It also provides insights about the potential benefits of active learning when compared with traditional, passive and teacher-centred methods of teaching & learning

See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights

Towards Flight Trials for an Autonomous UAV Emergency Landing using Machine Vision

This paper presents the evolution and status of a number of research programs focussed on developing an automated fixed wing UAV landing system. Results obtained in each of the three main areas of research as vision-based site identification, path and trajectory planning and multi-criteria decision making are presented. The results obtained provide a baseline for further refinements and constitute the starting point for the implementation of a prototype system ready for flight testing

Vision-Based Path Finding Strategy of Unmanned Aerial Vehicles for Electrical Infrastructure Purpose

In this chapter we present the development of automated visual inspection systems for electrical infrastructure. The inspection is performed using images acquired with an unmanned aerial vehicle (UAV). Through automated inspection routes, the state of the infrastructure can be evaluated and then the appropriate correcting measures be taken. The monitoring of power lines can be done using passive sensors such as cameras or active sensors such as light detection and ranging (LIDAR) cameras, image processing techniques, computer vision and control systems can then be used. Additionally, a three-dimensional (3D) reconstruction process is possible using images either offline or during the monitoring. An UAV with an onboard embedded computer is used to execute the computer vision and path planning algorithms. The work done shows that the proposed strategy aids in the automation of power line inspection

Control visual de un vehiculo aereo autonomo usando deteccion y seguimiento de caracterısticas en espacios exteriores

The main goal of this thesis is to build vision-guided autonomous flying robots. Tasks like feature detection, target tracking, obstacle avoidance using vision sensors allows such robots to serve as intelligent eyes-in-the-sky suitable for numerous applications including law enforcement, search and rescue, aerial mapping and inspection, and movie making. Furthermore, computer vision may reduce uncertainty and increase versatility and overall accuracy of robotic tasks which are important concerns in most applications. We address the visual servoing problem for an Unmanned Aerial Vehicle (UAV) in outdoor environments, specifically an autonomous robotic helicopter. We propose vision-based techniques which allow an UAV to perform maneuvers towards features of interest when GPS has dropouts (usually in urban areas) or to track a target. We investigate visual servo control techniques that use velocities of suitable image features parameters directly to compute the references for the flight control for driving the robot, i.e, the tasks is specified directly in the sensor workspace. Therefore, the strategy does not require camera calibration procedures or 3D scene reconstruction schemes which are subject to errors and demand high processing power. Although visual servoing is a well studied problem for ground-based robots or robotics manipulators operating in 2D environments, is not well studied for the visual control problem of an UAV such as the one proposed in this thesis. The approach proposed here was analyzed and validated using several experimental tests on different platforms. We investigate a number of factors that influence the performance of the system including processing frame rate, vibrations, control strategies and environmental conditions such as light and luminance, background changes, etc. Experiments on the real autonomous helicopter show that visual servoing approach can be used to control the displacements of an autonomous helicopter vertically, laterally and longitudinally, and can be used to both, track an external target and guide the UAV trajectory

The Avoidance Spectrum of Alexandroff Spaces

In this paper we prove that every T0 Alexandroff topological space (, ) is homeomorphic to the avoidance of a subspace of (Spec(Λ), ), where Spec(Λ) denotes the prime spectrum of a semi-ring Λ induced by , and is the Zariski topology. We also prove that (Spec(Λ), ) is an Alexandroff space if and only if Λ satisfies the Gilmer property

Aerial Object Following Using Visual Fuzzy Servoing

This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigatio

A Mobile Memory Game for Patients with Acquired Brain Damage: A Preliminary Usability Study

Memory rehabilitation and training is an important activity for patients with Acquired Brain Damage, including Cerebral Vascular Accident (stroke) and Traumatic Brain Injury patients. Although many interactive web-based and computer applications have been developed, the use of mobile devices apps has not been sufficiently studied from the point of view of its usability for these users. In this paper, a preliminary usability and accessibility study of a memory game for mobile devices (developed from scratch under Android OS) is presented. This study, based on the Shadow Expert Technique, allows improving the prototype and provides useful hints for increasing acceptability of Android applications, not only by Acquired Brain Damage patients but also by other people with cognitive disorders.Ministerio de Ciencia e Innovación PROCUR@-IPT-2011-1038-900000European Project GameUp AAL-2011-4-09