The augmented reality framework : an approach to the rapid creation of mixed reality environments and testing scenarios

Debugging errors during real-world testing of remote platforms can be time consuming and expensive when the remote environment is inaccessible and hazardous such as deep-sea. Pre-real world testing facilities, such as Hardware-In-the-Loop (HIL), are often not available due to the time and expense necessary to create them. Testing facilities tend to be monolithic in structure and thus inflexible making complete redesign necessary for slightly different uses. Redesign is simpler in the short term than creating the required architecture for a generic facility. This leads to expensive facilities, due to reinvention of the wheel, or worse, no testing facilities. Without adequate pre-real world testing, integration errors can go undetected until real world testing where they are more costly to diagnose and rectify, e.g. especially when developing Unmanned Underwater Vehicles (UUVs). This thesis introduces a novel framework, the Augmented Reality Framework (ARF), for rapid construction of virtual environments for Augmented Reality tasks such as Pure Simulation, HIL, Hybrid Simulation and real world testing. ARF’s architecture is based on JavaBeans and is therefore inherently generic, flexible and extendable. The aim is to increase the performance of constructing, reconfiguring and extending virtual environments, and consequently enable more mature and stable systems to be developed in less time due to previously undetectable faults being diagnosed earlier in the pre-real-world testing phase. This is only achievable if test harnesses can be created quickly and easily, which in turn allows the developer to visualise more system feedback making faults easier to spot. Early fault detection and less wasted real world testing leads to a more mature, stable and less expensive system. ARF provides guidance on how to connect and configure user made components, allowing for rapid prototyping and complex virtual environments to be created quickly and easily. In essence, ARF tries to provide intuitive construction guidance which is similar in nature to LEGOR pieces which can be so easily connected to form useful configurations. ARF is demonstrated through case studies which show the flexibility and applicability of ARF to testing techniques such as HIL for UUVs. In addition, an informal study was carried out to asses the performance increases attributable to ARF’s core concepts. In comparison to classical programming methods ARF’s average performance increase was close to 200%. The study showed that ARF was incredibly intuitive since the test subjects were novices in ARF but experts in programming. ARF provides key contributions in the field of HIL testing of remote systems by providing more accessible facilities that allow new or modified testing scenarios to be created where it might not have been feasible to do so before. In turn this leads to early detection of faults which in some cases would not have ever been detected before

A Comparison of Different Cognitive Paradigms Using Simple Animats in a Virtual Laboratory, with Implications to the Notion of Cognition

In this thesis I present a virtual laboratory which implements five different models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no best model, since different models are better for different things in different contexts. The models I chose, although quite simple, represent different approaches for studying cognition. Using the results as an empirical philosophical aid, I note that there is no best approach for studying cognition, since different approaches have all advantages and disadvantages, because they study different aspects of cognition from different contexts. This has implications for current debates on proper approaches for cognition: all approaches are a bit proper, but none will be proper enough. I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition

Heterogeneous Self-Reconfiguring Robotics

Self-reconfiguring (SR) robots are modular systems that can autonomously change shape, or reconfigure, for increased versatility and adaptability in unknown environments. In this thesis, we investigate planning and control for systems of non-identical modules, known as heterogeneous SR robots. Although previous approaches rely on module homogeneity as a critical property, we show that the planning complexity of fundamental algorithmic problems in the heterogeneous case is equivalent to that of systems with identical modules. Primarily, we study the problem of how to plan shape changes while considering the placement of specific modules within the structure. We characterize this key challenge in terms of the amount of free space available to the robot and develop a series of decentralized reconfiguration planning algorithms that assume progressively more severe free space constraints and support reconfiguration among obstacles. In addition, we compose our basic planning techniques in different ways to address problems in the related task domains of positioning modules according to function, locomotion among obstacles, self-repair, and recognizing the achievement of distributed goal-states. We also describe the design of a novel simulation environment, implementation results using this simulator, and experimental results in hardware using a planar SR system called the Crystal Robot. These results encourage development of heterogeneous systems. Our algorithms enhance the versatility and adaptability of SR robots by enabling them to use functionally specialized components to match capability, in addition to shape, to the task at hand

Actas do 10º Encontro Português de Computação Gráfica

Actas do 10º Encontro Portugês de Computação Gráfica, Lisboa, 1-3 de Outubro de 2001A investigação, o desenvolvimento e o ensino na área da Computação Gráfica constituem, em Portugal, uma realidade positiva e de largas tradições. O Encontro Português de Computação Gráfica (EPCG), realizado no âmbito das actividades do Grupo Português de Computação Gráfica (GPCG), tem permitido reunir regularmente, desde o 1º EPCG realizado também em Lisboa, mas no já longínquo mês de Julho de 1988, todos os que trabalham nesta área abrangente e com inúmeras aplicações. Pela primeira vez no historial destes Encontros, o 10º EPCG foi organizado em ligação estreita com as comunidades do Processamento de Imagem e da Visão por Computador, através da Associação Portuguesa de Reconhecimento de Padrões (APRP), salientando-se, assim, a acrescida colaboração, e a convergência, entre essas duas áreas e a Computação Gráfica. Este é o livro de actas deste 10º EPCG.INSATUniWebIcep PortugalMicrografAutodes

Enhanced online programming for industrial robots

The use of robots and automation levels in the industrial sector is expected to grow, and is driven by the on-going need for lower costs and enhanced productivity. The manufacturing industry continues to seek ways of realizing enhanced production, and the programming of articulated production robots has been identified as a major area for improvement. However, realizing this automation level increase requires capable programming and control technologies. Many industries employ offline-programming which operates within a manually controlled and specific work environment. This is especially true within the high-volume automotive industry, particularly in high-speed assembly and component handling. For small-batch manufacturing and small to medium-sized enterprises, online programming continues to play an important role, but the complexity of programming remains a major obstacle for automation using industrial robots. Scenarios that rely on manual data input based on real world obstructions require that entire production systems cease for significant time periods while data is being manipulated, leading to financial losses. The application of simulation tools generate discrete portions of the total robot trajectories, while requiring manual inputs to link paths associated with different activities. Human input is also required to correct inaccuracies and errors resulting from unknowns and falsehoods in the environment. This study developed a new supported online robot programming approach, which is implemented as a robot control program. By applying online and offline programming in addition to appropriate manual robot control techniques, disadvantages such as manual pre-processing times and production downtimes have been either reduced or completely eliminated. The industrial requirements were evaluated considering modern manufacturing aspects. A cell-based Voronoi generation algorithm within a probabilistic world model has been introduced, together with a trajectory planner and an appropriate human machine interface. The robot programs so achieved are comparable to manually programmed robot programs and the results for a Mitsubishi RV-2AJ five-axis industrial robot are presented. Automated workspace analysis techniques and trajectory smoothing are used to accomplish this. The new robot control program considers the working production environment as a single and complete workspace. Non-productive time is required, but unlike previously reported approaches, this is achieved automatically and in a timely manner. As such, the actual cell-learning time is minimal

Learning to grasp and extract affordances: the Integrated Learning of Grasps and Affordances (ILGA) model

The activity of certain parietal neurons has been interpreted as encoding affordances (directly perceivable opportunities) for grasping. Separate computational models have been developed for infant grasp learning and affordance learning, but no single model has yet combined these processes in a neurobiologically plausible way. We present the Integrated Learning of Grasps and Affordances (ILGA) model that simultaneously learns grasp affordances from visual object features and motor parameters for planning grasps using trial-and-error reinforcement learning. As in the Infant Learning to Grasp Model, we model a stage of infant development prior to the onset of sophisticated visual processing of hand–object relations, but we assume that certain premotor neurons activate neural populations in primary motor cortex that synergistically control different combinations of fingers. The ILGA model is able to extract affordance representations from visual object features, learn motor parameters for generating stable grasps, and generalize its learned representations to novel objects

Fidelity optimization in distributed virtual environments

In virtual environment systems, the ultimate goal is delivery of the highest-fidelity user experience possible. This dissertation shows that is possible to increase the scalability of distributed virtual environments (DVEs), in a tractable fashion, through a novel application of optimization techniques. Fidelity is maximized by utilizing the given display and network capacity in an optimal fashion, individually tuned for multiple users, in a manner most appropriate to a specific DVE application. This optimization is accomplished using the QUICK framework for managing the display and request of representations for virtual objects. Ratings of representation Quality, object Importance, and representation Cost are included in model descriptions as special annotations. The QUICK optimization computes the fidelity contribution of a representation by combining these annotations with specifications of user task and platform capability. This dissertation contributes the QUICK optimization algorithms; a software framework for experimentation; and associated general purpose formats for codifying Quality, Importance, Cost, task, and platform capability. Experimentation with the QUICK framework has shown overwhelming advantages in comparison with standard resource management techniqueshttp://www.archive.org/details/fidelityoptimiza00cappCivilian author.Approved for public release; distribution is unlimited

Design and remote control of a Gantry mechanism for the SCARA robot

Remote experimentation and control have led researchers to develop new technologies as well as implement existing techniques. The multidisciplinary nature of research in electromechanical systems has led to the synergy of mechanical engineering, electrical engineering and computer science. This work describes the design of a model of a Gantry Mechanism, which maneuvers a web-cam. The user controls virtually the position of end-effecter of the Gantry Mechanism using a Graphical User Interface. The GUI is accessed over the Internet. In order to reduce the unbalanced vibrations of the Gantry Mechanism, we investigate the development of an algorithm of input shaping. A model of the Gantry Mechanism is built, and it is controlled over the Internet to view experimentation of the SCARA Robot. The system performance is studied by comparing the inputs such as distances and angles with outputs, and methods to improve the performance are suggested

Autonomous Vehicle Control

A practical knowledge base in the emerging field of Robotics was developed and used to create a framework for further experiments. The framework was designed such that modular parts could be replaced, allowing for future development without reinventing the wheel . To prove the framework, a semi-autonomous robot was implemented, including stereo vision sensors, an inertial navigation system, and a simultaneous localization and mapping algorithm