396 research outputs found
Quadrotor control for persistent surveillance of dynamic environments
Thesis (M.S.)--Boston UniversityThe last decade has witnessed many advances in the field of small scale unmanned aerial vehicles (UAVs). In particular, the quadrotor has attracted significant attention. Due to its ability to perform vertical takeoff and landing, and to operate in cluttered spaces, the quadrotor is utilized in numerous practical applications, such as reconnaissance and information gathering in unsafe or otherwise unreachable environments.
This work considers the application of aerial surveillance over a city-like environment. The thesis presents a framework for automatic deployment of quadrotors to monitor and react to dynamically changing events. The framework has a hierarchical structure. At the top level, the UAVs perform complex behaviors that satisfy high- level mission specifications. At the bottom level, low-level controllers drive actuators on vehicles to perform the desired maneuvers.
In parallel with the development of controllers, this work covers the implementation of the system into an experimental testbed. The testbed emulates a city using physical objects to represent static features and projectors to display dynamic events occurring on the ground as seen by an aerial vehicle. The experimental platform features a motion capture system that provides position data for UAVs and physical features of the environment, allowing for precise, closed-loop control of the vehicles. Experimental runs in the testbed are used to validate the effectiveness of the developed control strategies
How do learners respond to computer based learning material which has been designed to suit their particular learning style
The development of ICT in education has changed the nature of people's
learning. The evolution of Computer Based Learning (CBL) to virtual learning
has had a huge effect on learning methodology. Learning theories from
behaviourism, cognitivism and constructivism have been re-assessed. This
study explored students' feedback and experiences when using CBL
material which has been adapted to particular learning styles. Studies show
that individuals learn in different ways. They have different preferences in
collecting, organizing and delivering information. These differences impact
on learning outcomes. The framework in this study concerns itself with
modal preferences known as the VARK Model. The study focuses on CBL
material which has been designed for learning new software. This learning
material was designed with four different learning routes to appeal to those
with dominant Visual, Aural, Reading and Kinaesthetic preferences
respectively. The learning package was called the MINDs learning system.
Respondents involved were student teachers in two Universities in the UK
and Malaysia. Sixty two respondents agreed to participate interviews and in
trialling courseware. Data was collected through questionnaire, survey,
interview and observation. Quantitative and qualitative data was analysed
descriptively, triangulation of the findings was carried out and conclusions
were drawn. Findings from the study show that learning styles instruments
measure general preferences rather than offering an indication of the
specific context in which learning takes place. Matching learning material
with particular learning styles did not significantly increase motivation,
comprehension or have a major impact on learning. However, learners are
aware of having learning styles and found that learning with suited learning
preferences made them feel more comfortable. Recommendations were put
forward for future research to design and develop a 'new type' of CBL
material which takes into account individual learning preferences
PATH PLANNING STRATEGIES FOR VISIBILITY ENHANCEMENT WITH UNMANNED AERIAL VEHICLES IN CLUTTERED ENVIRONMENTS
Ph.DDOCTOR OF PHILOSOPH
Optimal Multi-UAV Trajectory Planning for Filming Applications
Teams of multiple Unmanned Aerial Vehicles (UAVs) can be used to record large-scale
outdoor scenarios and complementary views of several action points as a promising
system for cinematic video recording. Generating the trajectories of the UAVs plays
a key role, as it should be ensured that they comply with requirements for system
dynamics, smoothness, and safety. The rise of numerical methods for nonlinear
optimization is finding a
ourishing field in optimization-based approaches to multi-
UAV trajectory planning. In particular, these methods are rather promising for
video recording applications, as they enable multiple constraints and objectives to
be formulated, such as trajectory smoothness, compliance with UAV and camera
dynamics, avoidance of obstacles and inter-UAV con
icts, and mutual UAV visibility.
The main objective of this thesis is to plan online trajectories for multi-UAV teams in
video applications, formulating novel optimization problems and solving them in real
time.
The thesis begins by presenting a framework for carrying out autonomous cinematography
missions with a team of UAVs. This framework enables media directors
to design missions involving different types of shots with one or multiple cameras,
running sequentially or concurrently. Second, the thesis proposes a novel non-linear
formulation for the challenging problem of computing optimal multi-UAV trajectories
for cinematography, integrating UAV dynamics and collision avoidance constraints,
together with cinematographic aspects such as smoothness, gimbal mechanical limits,
and mutual camera visibility. Lastly, the thesis describes a method for autonomous
aerial recording with distributed lighting by a team of UAVs. The multi-UAV trajectory
optimization problem is decoupled into two steps in order to tackle non-linear cinematographic aspects and obstacle avoidance at separate stages. This allows the
trajectory planner to perform in real time and to react online to changes in dynamic
environments.
It is important to note that all the methods in the thesis have been validated
by means of extensive simulations and field experiments. Moreover, all the software
components have been developed as open source.Los equipos de vehículos aéreos no tripulados (UAV) son sistemas prometedores para grabar
eventos cinematográficos, en escenarios exteriores de grandes dimensiones difíciles de cubrir
o para tomar vistas complementarias de diferentes puntos de acción. La generación de
trayectorias para este tipo de vehículos desempeña un papel fundamental, ya que debe
garantizarse que se cumplan requisitos dinámicos, de suavidad y de seguridad.
Los enfoques basados en la optimización para la planificación de trayectorias de múltiples
UAVs se pueden ver beneficiados por el auge de los métodos numéricos para la resolución de
problemas de optimización no lineales. En particular, estos métodos son bastante
prometedores para las aplicaciones de grabación de vídeo, ya que permiten formular múltiples
restricciones y objetivos, como la suavidad de la trayectoria, el cumplimiento de la dinámica
del UAV y de la cámara, la evitación de obstáculos y de conflictos entre UAVs, y la visibilidad
mutua.
El objetivo principal de esta tesis es planificar trayectorias para equipos multi-UAV en
aplicaciones de vídeo, formulando novedosos problemas de optimización y resolviéndolos en
tiempo real.
La tesis comienza presentando un marco de trabajo para la realización de misiones
cinematográficas autónomas con un equipo de UAVs. Este marco permite a los directores de
medios de comunicación diseñar misiones que incluyan diferentes tipos de tomas con una o
varias cámaras, ejecutadas de forma secuencial o concurrente. En segundo lugar, la tesis
propone una novedosa formulación no lineal para el difícil problema de calcular las
trayectorias óptimas de los vehículos aéreos no tripulados en cinematografía, integrando en el
problema la dinámica de los UAVs y las restricciones para evitar colisiones, junto con aspectos
cinematográficos como la suavidad, los límites mecánicos del cardán y la visibilidad mutua de
las cámaras. Por último, la tesis describe un método de grabación aérea autónoma con
iluminación distribuida por un equipo de UAVs. El problema de optimización de trayectorias se
desacopla en dos pasos para abordar los aspectos cinematográficos no lineales y la evitación
de obstáculos en etapas separadas. Esto permite al planificador de trayectorias actuar en
tiempo real y reaccionar en línea a los cambios en los entornos dinámicos.
Es importante señalar que todos los métodos de la tesis han sido validados mediante extensas
simulaciones y experimentos de campo. Además, todos los componentes del software se han
desarrollado como código abierto
3D Real-Time Energy Efficient Path Planning for a Fleet of Fixed-Wing UAVs
UAV path planning requires finding an optimal (or sub-optimal) collision free path in a cluttered environment, while taking into account geometric, physical and temporal constraints, eventually allowing UAVs to perform their tasks despite several uncertainty sources. This paper reviews the current state-of-the-art in path planning, and subsequently introduces a novel node-based algorithm based on the called EEA*. EEA* is based on the A* Search algorithm and aims at mitigating some of its key limitations. The proposed EEA* deals with 3D environments, it provides robustness quickly converging to the solution, it is energy efficient and it is realtime implementable and executable. Along with the proposed EEA*, a local path planner is developed to cope with unknown dynamic threats in the environment. Applicability and effectiveness is first demonstrated via simulated experiments using a fixed-wing UAV that operates in different mountain-like 3D environments in the presence of several unknown dynamic obstacles. Then, the algorithm is applied in a multi-agent setting with three UAVs that are commanded to follow their respective paths in a safe way. The energy efficiency of the EEA* algorithm has also been tested and compared with the conventional A* algorithm
Reducing Object Detection Uncertainty from RGB and Thermal Data for UAV Outdoor Surveillance
Recent advances in Unmanned Aerial Vehicles (UAVs) have resulted in their
quick adoption for wide a range of civilian applications, including precision
agriculture, biosecurity, disaster monitoring and surveillance. UAVs offer
low-cost platforms with flexible hardware configurations, as well as an
increasing number of autonomous capabilities, including take-off, landing,
object tracking and obstacle avoidance. However, little attention has been paid
to how UAVs deal with object detection uncertainties caused by false readings
from vision-based detectors, data noise, vibrations, and occlusion. In most
situations, the relevance and understanding of these detections are delegated
to human operators, as many UAVs have limited cognition power to interact
autonomously with the environment. This paper presents a framework for
autonomous navigation under uncertainty in outdoor scenarios for small UAVs
using a probabilistic-based motion planner. The framework is evaluated with
real flight tests using a sub 2 kg quadrotor UAV and illustrated in victim
finding Search and Rescue (SAR) case study in a forest/bushland. The navigation
problem is modelled using a Partially Observable Markov Decision Process
(POMDP), and solved in real time onboard the small UAV using Augmented Belief
Trees (ABT) and the TAPIR toolkit. Results from experiments using colour and
thermal imagery show that the proposed motion planner provides accurate victim
localisation coordinates, as the UAV has the flexibility to interact with the
environment and obtain clearer visualisations of any potential victims compared
to the baseline motion planner. Incorporating this system allows optimised UAV
surveillance operations by diminishing false positive readings from
vision-based object detectors
- …