1,172 research outputs found
Research and Education in Computational Science and Engineering
Over the past two decades the field of computational science and engineering
(CSE) has penetrated both basic and applied research in academia, industry, and
laboratories to advance discovery, optimize systems, support decision-makers,
and educate the scientific and engineering workforce. Informed by centuries of
theory and experiment, CSE performs computational experiments to answer
questions that neither theory nor experiment alone is equipped to answer. CSE
provides scientists and engineers of all persuasions with algorithmic
inventions and software systems that transcend disciplines and scales. Carried
on a wave of digital technology, CSE brings the power of parallelism to bear on
troves of data. Mathematics-based advanced computing has become a prevalent
means of discovery and innovation in essentially all areas of science,
engineering, technology, and society; and the CSE community is at the core of
this transformation. However, a combination of disruptive
developments---including the architectural complexity of extreme-scale
computing, the data revolution that engulfs the planet, and the specialization
required to follow the applications to new frontiers---is redefining the scope
and reach of the CSE endeavor. This report describes the rapid expansion of CSE
and the challenges to sustaining its bold advances. The report also presents
strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie
Visual attention and swarm cognition for off-road robots
Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2011Esta tese aborda o problema da modelação de atenção visual no contexto de robôs autónomos todo-o-terreno. O objectivo de utilizar mecanismos de atenção visual é o de focar a percepção nos aspectos do ambiente mais relevantes à tarefa do robô. Esta tese mostra que, na detecção de obstáculos e de trilhos, esta capacidade promove robustez e parcimónia computacional. Estas são características chave para a rapidez e eficiência dos robôs todo-o-terreno. Um dos maiores desafios na modelação de atenção visual advém da necessidade de gerir o compromisso velocidade-precisão na presença de variações de contexto ou de tarefa. Esta tese mostra que este compromisso é resolvido se o processo de atenção visual for modelado como um processo auto-organizado, cuja operação é modulada pelo módulo de selecção de acção, responsável pelo controlo do robô. Ao fechar a malha entre o processo de selecção de acção e o de percepção, o último é capaz de operar apenas onde é necessário, antecipando as acções do robô. Para fornecer atenção visual com propriedades auto-organizadas, este trabalho obtém inspiração da Natureza. Concretamente, os mecanismos responsáveis pela capacidade que as formigas guerreiras têm de procurar alimento de forma auto-organizada, são usados como metáfora na resolução da tarefa de procurar, também de forma auto-organizada, obstáculos e trilhos no campo visual do robô. A solução proposta nesta tese é a de colocar vários focos de atenção encoberta a operar como um enxame, através de interacções baseadas em feromona. Este trabalho representa a primeira realização corporizada de cognição de enxame. Este é um novo campo de investigação que procura descobrir os princípios básicos da cognição, inspeccionando as propriedades auto-organizadas da inteligência colectiva exibida pelos insectos sociais. Logo, esta tese contribui para a robótica como disciplina de engenharia e para a robótica como disciplina de modelação, capaz de suportar o estudo do comportamento adaptável.Esta tese aborda o problema da modelação de atenção visual no contexto de robôs autónomos
todo-o-terreno. O objectivo de utilizar mecanismos de atenção visual é o de focar a percepção
nos aspectos do ambiente mais relevantes à tarefa do robô. Esta tese mostra que, na detecção de
obstáculos e de trilhos, esta capacidade promove robustez e parcimónia computacional. Estas
são características chave para a rapidez e eficiência dos robôs todo-o-terreno.
Um dos maiores desafios na modelação de atenção visual advém da necessidade de gerir o
compromisso velocidade-precisão na presença de variações de contexto ou de tarefa. Esta tese
mostra que este compromisso é resolvido se o processo de atenção visual for modelado como
um processo auto-organizado, cuja operação é modulada pelo módulo de selecção de acção,
responsável pelo controlo do robô. Ao fechar a malha entre o processo de selecção de acção e
o de percepção, o último é capaz de operar apenas onde é necessário, antecipando as acções do
robô.
Para fornecer atenção visual com propriedades auto-organizadas, este trabalho obtém inspi-
ração da Natureza. Concretamente, os mecanismos responsáveis pela capacidade que as formi-
gas guerreiras têm de procurar alimento de forma auto-organizada, são usados como metáfora
na resolução da tarefa de procurar, também de forma auto-organizada, obstáculos e trilhos no
campo visual do robô. A solução proposta nesta tese é a de colocar vários focos de atenção
encoberta a operar como um enxame, através de interacções baseadas em feromona.
Este trabalho representa a primeira realização corporizada de cognição de enxame. Este é
um novo campo de investigação que procura descobrir os princípios básicos da cognição, ins-
peccionando as propriedades auto-organizadas da inteligência colectiva exibida pelos insectos
sociais. Logo, esta tese contribui para a robótica como disciplina de engenharia e para a robótica
como disciplina de modelação, capaz de suportar o estudo do comportamento adaptável.Fundação para a Ciência e a Tecnologia (FCT,SFRH/BD/27305/2006); Laboratory of Agent Modelling (LabMag
Swarming Reconnaissance Using Unmanned Aerial Vehicles in a Parallel Discrete Event Simulation
Current military affairs indicate that future military warfare requires safer, more accurate, and more fault-tolerant weapons systems. Unmanned Aerial Vehicles (UAV) are one answer to this military requirement. Technology in the UAV arena is moving toward smaller and more capable systems and is becoming available at a fraction of the cost. Exploiting the advances in these miniaturized flying vehicles is the aim of this research. How are the UAVs employed for the future military? The concept of operations for a micro-UAV system is adopted from nature from the appearance of flocking birds, movement of a school of fish, and swarming bees among others. All of these natural phenomena have a common thread: a global action resulting from many small individual actions. This emergent behavior is the aggregate result of many simple interactions occurring within the flock, school, or swarm. In a similar manner, a more robust weapon system uses emergent behavior resulting in no weakest link because the system itself is made up of simple interactions by hundreds or thousands of homogeneous UAVs. The global system in this research is referred to as a swarm. Losing one or a few individual unmanned vehicles would not dramatically impact the swarms ability to complete the mission or cause harm to any human operator. Swarming reconnaissance is the emergent behavior of swarms to perform a reconnaissance operation. An in-depth look at the design of a reconnaissance swarming mission is studied. A taxonomy of passive reconnaissance applications is developed to address feasibility. Evaluation of algorithms for swarm movement, communication, sensor input/analysis, targeting, and network topology result in priorities of each model\u27s desired features. After a thorough selection process of available implementations, a subset of those models are integrated and built upon resulting in a simulation that explores the innovations of swarming UAVs
Teaching control theory in high school
Controls is increasingly central to technology, science, and society, yet remains the “hidden technology.” Our appropriate emphasis on mathematical rigor and practical relevance in the past 40 years has not been similarly balanced with technical accessibility. The aim of this tutorial is to enlist the controls community in helping to radically rethink controls education. In addition to the brief 2 hour tutorial at CDC, we will have a website with additional materials, but particularly extensive online videos with mathematical details and case studies. We will also have a booth in the exhibition area at CDC with live demos and engaging competitions throughout the conference
Bio-inspired Neural Networks for Angular Velocity Estimation in Visually Guided Flights
Executing delicate flight maneuvers using visual information is a huge challenge
for future robotic vision systems. As a source of inspiration, insects are quite apt at
navigating in woods and landing on surfaces which require delicate visual perception
and flight control. The exquisite sensitivity of insects for image motion speed, as revealed recently, is coming from a class of specific neurons called descending neurons.
Some of the descending neurons have demonstrated angular velocity selectivity as the
image motion speed varies in retina. Build a quantitative angular velocity detection
model is the first step for not only further understanding of the biological visual system, but also providing robust and economic solutions of visual motion perception
for an artificial visual system. This thesis aims to explore biological image processing
methods for motion speed detection in visually guided flights. The major contributions
are summarized as follows.
We have presented an angular velocity decoding model (AVDM), which estimates
the visual motion speed combining both textural and temporal information from input signals. The model consists of three parts: elementary motion detection circuits,
wide-field texture estimation pathway and angular velocity decoding layer. The model
estimates the angular velocity very well with improved spatial frequency independence
compared to the state-of-the-art angular velocity detecting models, when firstly tested by moving sinusoidal gratings. This spatial independence is vital to account for
the honeybee’s flight behaviors. We have also investigated the spatial and temporal
resolutions of honeybees to get a bio-plausible parameter setting for explaining these
behaviors.
To investigate whether the model can account for observations of tunnel centering
behaviors of honeybees, the model has been implemented in a virtual bee simulated by
the game engine Unity. The simulation results of a series of experiments show that the
agent can adjust its position to fly through patterned tunnels by balancing the angular
velocities estimated on both eyes under several circumstances. All tunnel stimulations
reproduce similar behaviors of real bees, which indicate that our model does provide
a possible explanation for estimating the image velocity and can be used for MAV’s
flight course regulation in tunnels. What’s more, to further verify the robustness of the
model, the visually guided terrain following simulations have been carried out with a
closed-loop control scheme to restore a preset angular velocity during the flight. The
simulation results of successfully flying over the undulating terrain verify the feasibility and robustness of the AVDM performing in various application scenarios, which
shows its potential in applications of micro aerial vehicle’s terrain following.
In addition, we have also applied the AVDM in grazing landing using only visual
information. A LGMD neuron is also introduced to avoid collision and to trigger the
hover phase, which ensures the safety of landing. By applying honeybee’s landing
strategy of keeping constant angular velocity, we have designed a close-loop control
scheme with an adaptive gain to control landing dynamic using AVDM response as
input. A series of controlled trails have been designed in Unity platform to demonstrate
the effectiveness of the proposed model and control scheme for visual landing under
various conditions. The proposed model could be implemented into real small robots
to investigate the robustness in real landing scenarios in near future
Recommended from our members
Design, Deployment, Navigation, and Control of Mobile Robots for Perception and Sensor Data Collection
Aerial robots, including rotary-wing and fixed-wing unmanned aerial vehicles or UAVs, have shown great capabilities in surveying as well as search and rescue from above. However, either rotary-wing or fixed-wing UAVs have nearly insoluble flaws. In order to overcome the under-actuating nature of multi-rotor UAVs, Chapter 2 proposes modeling methods and control schemes for fully-actuated hexacopters. Additionally, rotary-wing robots suffer from limited battery life as well as lack of fail-safe mechanism upon losing motors, while fixed-wing robots lacks the ability to take off and land vertically. Therefore, Chapter 4 proposes a bio-inpired hybrid aerial robot to extend mutli-rotor flight time and fail-safe capability and provide fixed-wing glider with vertical take-off and landing or VTOL capability. Moreover, to extend the flight time and optimize the energy consumption of multi-rotor UAVs, Chapter 3 proposes a multi-disciplinary design optimization based flight trajectory optimizer involving linear rotor inflow models to reduce flight time or energy consumption of specific missions.In terms of unmanned ground vehicles or UGVs used for perception and mapping, there has been a research gap to provide a low-cost, highly agile over-actuated chassis design. Chapter 5 proposes a 3D-printable double Ackermann steering chassis design with 2-wheel standing and balancing capability to fill in this gap. Chapter 6, on the other hand, proposes the system design of a UGV capable of performing perception and mapping in a limited lighting, unstructured, and GPS-denied environment based on a nevertheless nonholonomic chassis, where primary concern becomes the reliability in performing real-time mapping and preservation of solely static environment.The last but not least topic discussed in this dissertation is to promote the role of UAV imagery in earthquake response. In Chapter 7 we combine the traditional UAV plan view perspective with north and east elevation view video data to provide motion estimation in all 6 degrees of freedom, as well as proposing Video Transformer for motion tracking.All in all, with attempts to expand and promote the designs, deployment and control schemes of both aerial and ground mobile robots, this dissertation strives to provide case study results and state-of-the-art methods for future robotics studies
Organisation of foraging in ants
In social insects, foraging is often cooperative, and so requires considerable organisation. In most ants, organisation is a bottom-up process where decisions taken by individuals result in emergent colony level patterns. Individuals base their decisions on their internal state, their past experience, and their environment. By depositing trail pheromones, for example, ants can alter the environment, and thus affect the behaviour of their nestmates. The development of emergent patterns depends on both how individuals affect the environment, and how they react to changes in the environment.
Chapters 4 – 9 investigate the role of trail pheromones and route memory in the ant Lasius niger. Route memories can form rapidly and be followed accurately, and when route memories and trail pheromones contradict each other, ants overwhelmingly follow route memories (chapter 4). Route memories and trail pheromones can also interact synergistically, allowing ants to forage faster without sacrificing accuracy (chapter 5). Home range markings also interact with other information sources to affect ant behaviour (chapter 6). Trail pheromones assist experienced ants when facing complex, difficult-to-learn routes (chapter 7). When facing complicated routes, ants deposit more pheromone to assist in navigation and learning (chapter 7). Deposition of trail pheromones is suppressed by ants leaving a marked path (chapter 5), strong pheromone trails (chapter 7) and trail crowding (chapter 8). Colony level ‘decisions’ can be driven by factors other than trail pheromones, such as overcrowding at a food source (chapter 9). Chapter 10 reviews the many roles of trail pheromones in ants.
Chapters 11 – 14 focus on the organisation of cooperative food retrieval. Pheidole oxyops workers arrange themselves non-randomly around items to increase transport speeds (chapter 11). Groups of ants will rotate food items to reduce drag (chapter 12). Chapters 13 and 14 encompass the ecology of cooperative transport, and how it has shaped trail pheromone recruitment in P. oxyops and Paratrechina longicornis. Lastly, chapter 15 provide a comprehensive review of cooperative transport in ants and elsewhere
Control and communication systems for automated vehicles cooperation and coordination
Mención Internacional en el título de doctorThe technological advances in the Intelligent Transportation Systems (ITS) are exponentially
improving over the last century. The objective is to provide intelligent and innovative services
for the different modes of transportation, towards a better, safer, coordinated and smarter
transport networks. The Intelligent Transportation Systems (ITS) focus is divided into two
main categories; the first is to improve existing components of the transport networks, while
the second is to develop intelligent vehicles which facilitate the transportation process. Different
research efforts have been exerted to tackle various aspects in the fields of the automated
vehicles. Accordingly, this thesis is addressing the problem of multiple automated vehicles
cooperation and coordination. At first, 3DCoAutoSim driving simulator was developed
in Unity game engine and connected to Robot Operating System (ROS) framework and
Simulation of Urban Mobility (SUMO). 3DCoAutoSim is an abbreviation for "3D Simulator
for Cooperative Advanced Driver Assistance Systems (ADAS) and Automated Vehicles
Simulator". 3DCoAutoSim was tested under different circumstances and conditions, afterward,
it was validated through carrying-out several controlled experiments and compare
the results against their counter reality experiments. The obtained results showed the efficiency
of the simulator to handle different situations, emulating real world vehicles. Next
is the development of the iCab platforms, which is an abbreviation for "Intelligent Campus
Automobile". The platforms are two electric golf-carts that were modified mechanically, electronically
and electrically towards the goal of automated driving. Each iCab was equipped
with several on-board embedded computers, perception sensors and auxiliary devices, in
order to execute the necessary actions for self-driving. Moreover, the platforms are capable
of several Vehicle-to-Everything (V2X) communication schemes, applying three layers of
control, utilizing cooperation architecture for platooning, executing localization systems,
mapping systems, perception systems, and finally several planning systems. Hundreds of
experiments were carried-out for the validation of each system in the iCab platform. Results
proved the functionality of the platform to self-drive from one point to another with minimal
human intervention.Los avances tecnológicos en Sistemas Inteligentes de Transporte (ITS) han crecido de forma
exponencial durante el último siglo. El objetivo de estos avances es el de proveer de sistemas
innovadores e inteligentes para ser aplicados a los diferentes medios de transporte, con el fin
de conseguir un transporte mas eficiente, seguro, coordinado e inteligente. El foco de los ITS
se divide principalmente en dos categorías; la primera es la mejora de los componentes ya
existentes en las redes de transporte, mientras que la segunda es la de desarrollar vehículos
inteligentes que hagan más fácil y eficiente el transporte. Diferentes esfuerzos de investigación
se han llevado a cabo con el fin de solucionar los numerosos aspectos asociados con
la conducción autónoma. Esta tesis propone una solución para la cooperación y coordinación
de múltiples vehículos. Para ello, en primer lugar se desarrolló un simulador (3DCoAutoSim)
de conducción basado en el motor de juegos Unity, conectado al framework Robot Operating
System (ROS) y al simulador Simulation of Urban Mobility (SUMO). 3DCoAutoSim ha
sido probado en diferentes condiciones y circunstancias, para posteriormente validarlo con
resultados a través de varios experimentos reales controlados. Los resultados obtenidos
mostraron la eficiencia del simulador para manejar diferentes situaciones, emulando los
vehículos en el mundo real. En segundo lugar, se desarrolló la plataforma de investigación
Intelligent Campus Automobile (iCab), que consiste en dos carritos eléctricos de golf, que
fueron modificados eléctrica, mecánica y electrónicamente para darle capacidades autónomas.
Cada iCab se equipó con diferentes computadoras embebidas, sensores de percepción y
unidades auxiliares, con la finalidad de transformarlos en vehículos autónomos. Además,
se les han dado capacidad de comunicación multimodal (V2X), se les han aplicado tres
capas de control, incorporando una arquitectura de cooperación para operación en modo
tren, diferentes esquemas de localización, mapeado, percepción y planificación de rutas.
Innumerables experimentos han sido realizados para validar cada uno de los diferentes sistemas
incorporados. Los resultados prueban la funcionalidad de esta plataforma para realizar
conducción autónoma y cooperativa con mínima intervención humana.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Francisco Javier Otamendi Fernández de la Puebla.- Secretario: Hanno Hildmann.- Vocal: Pietro Cerr
Perception and intelligent localization for autonomous driving
Mestrado em Engenharia de Computadores e TelemáticaVisão por computador e fusão sensorial são temas relativamente recentes, no entanto largamente adoptados no desenvolvimento de robôs autónomos que exigem adaptabilidade ao seu ambiente envolvente. Esta dissertação foca-se numa abordagem a estes dois temas para alcançar percepção no contexto de condução autónoma. O uso de câmaras para atingir este fim é um
processo bastante complexo. Ao contrário dos meios sensoriais clássicos que fornecem sempre o mesmo tipo de informação precisa e atingida de forma determinística, as sucessivas imagens adquiridas por uma câmara estão repletas
da mais variada informação e toda esta ambígua e extremamente difícil de extrair. A utilização de câmaras como meio sensorial em robótica
é o mais próximo que chegamos na semelhança com aquele que é o de maior importância no processo de percepção humana, o sistema de visão. Visão por computador é uma disciplina científica que engloba àreas como: processamento
de sinal, inteligência artificial, matemática, teoria de controlo, neurobiologia e física.
A plataforma de suporte ao estudo desenvolvido no âmbito desta dissertação é o ROTA (RObô Triciclo Autónomo) e todos os elementos que consistem
o seu ambiente. No contexto deste, são descritas abordagens que foram introduzidas com fim de desenvolver soluções para todos os desafios que o
robô enfrenta no seu ambiente: detecção de linhas de estrada e consequente percepção desta, detecção de obstáculos, semáforos, zona da passadeira e zona de obras. É também descrito um sistema de calibração e aplicação da remoção da perspectiva da imagem, desenvolvido de modo a mapear os elementos percepcionados em distâncias reais. Em consequência do sistema
de percepção, é ainda abordado o desenvolvimento de auto-localização integrado
numa arquitectura distribuída incluindo navegação com planeamento inteligente. Todo o trabalho desenvolvido no decurso da dissertação é essencialmente centrado no desenvolvimento de percepção robótica no contexto de condução autónoma.Computer vision and sensor fusion are subjects that are quite recent, however widely adopted in the development of autonomous robots that require
adaptability to their surrounding environment. This thesis gives an approach on both in order to achieve perception in the scope of autonomous driving.
The use of cameras to achieve this goal is a rather complex subject.
Unlike the classic sensorial devices that provide the same type of information with precision and achieve this in a deterministic way, the successive
images acquired by a camera are replete with the most varied information, that this ambiguous and extremely dificult to extract. The use of cameras
for robotic sensing is the closest we got within the similarities with what is of most importance in the process of human perception, the vision system. Computer vision is a scientific discipline that encompasses areas such as signal processing, artificial intelligence, mathematics, control theory,
neurobiology and physics.
The support platform in which the study within this thesis was developed, includes ROTA (RObô Triciclo Autónomo) and all elements comprising its
environment. In its context, are described approaches that introduced in the platform in order to develop solutions for all the challenges facing the robot in its environment: detection of lane markings and its consequent perception, obstacle detection, trafic lights, crosswalk and road maintenance area. It is also described a calibration system and implementation for the removal of the image perspective, developed in order to map the
elements perceived in actual real world distances. As a result of the perception system development, it is also addressed self-localization integrated in
a distributed architecture that allows navigation with long term planning.
All the work developed in the course of this work is essentially focused on robotic perception in the context of autonomous driving
A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future
A High Altitude Platform Station (HAPS) is a network node that operates in
the stratosphere at an of altitude around 20 km and is instrumental for
providing communication services. Precipitated by technological innovations in
the areas of autonomous avionics, array antennas, solar panel efficiency
levels, and battery energy densities, and fueled by flourishing industry
ecosystems, the HAPS has emerged as an indispensable component of
next-generations of wireless networks. In this article, we provide a vision and
framework for the HAPS networks of the future supported by a comprehensive and
state-of-the-art literature review. We highlight the unrealized potential of
HAPS systems and elaborate on their unique ability to serve metropolitan areas.
The latest advancements and promising technologies in the HAPS energy and
payload systems are discussed. The integration of the emerging Reconfigurable
Smart Surface (RSS) technology in the communications payload of HAPS systems
for providing a cost-effective deployment is proposed. A detailed overview of
the radio resource management in HAPS systems is presented along with
synergistic physical layer techniques, including Faster-Than-Nyquist (FTN)
signaling. Numerous aspects of handoff management in HAPS systems are
described. The notable contributions of Artificial Intelligence (AI) in HAPS,
including machine learning in the design, topology management, handoff, and
resource allocation aspects are emphasized. The extensive overview of the
literature we provide is crucial for substantiating our vision that depicts the
expected deployment opportunities and challenges in the next 10 years
(next-generation networks), as well as in the subsequent 10 years
(next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial
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