291 resultados para Symposium


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Piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes. Dimensional adjustments of adaptive polymer films are achieved via charge deposition and require a detailed understanding of the piezoelectric material responses which are expected to suffer due to strong vacuum UV, gamma, X-ray, energetic particles and atomic oxygen under low earth orbit exposure conditions. The degradation of PVDF and its copolymers under various stress environments has been investigated. Initial radiation aging studies using gamma- and e-beam irradiation have shown complex material changes with significant crosslinking, lowered melting and Curie points (where observable), effects on crystallinity, but little influence on overall piezoelectric properties. Surprisingly, complex aging processes have also been observed in elevated temperature environments with annealing phenomena and cyclic stresses resulting in thermal depoling of domains. Overall materials performance appears to be governed by a combination of chemical and physical degradation processes. Molecular changes are primarily induced via radiative damage, and physical damage from temperature and AO exposure is evident as depoling and surface erosion. Major differences between individual copolymers have been observed providing feedback on material selection strategies.

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The previous investigations have shown that the modal strain energy correlation method, MSEC, could successfully identify the damage of truss bridge structures. However, it has to incorporate the sensitivity matrix to estimate damage and is not reliable in certain damage detection cases. This paper presents an improved MSEC method where the prediction of modal strain energy change vector is differently obtained by running the eigensolutions on-line in optimisation iterations. The particular trail damage treatment group maximising the fitness function close to unity is identified as the detected damage location. This improvement is then compared with the original MSEC method along with other typical correlation-based methods on the finite element model of a simple truss bridge. The contributions to damage detection accuracy of each considered mode is also weighed and discussed. The iterative searching process is operated by using genetic algorithm. The results demonstrate that the improved MSEC method suffices the demand in detecting the damage of truss bridge structures, even when noised measurement is considered.

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Transport Certification Australia Limited, jointly with the National Transport Commission, has undertaken a project to investigate the feasibility of on-board mass monitoring (OBM) devices for regulatory purposes. OBM increases jurisdictional confidence in operational heavy vehicle compliance. This paper covers technical issues regarding potential use of dynamic data from OBM systems to indicate that tampering has occurred. Tamper-evidence and accuracy of current OBM systems needed to be determined before any regulatory schemes were put in place for its use. Tests performed to determine potential for, and ease of, tampering. An algorithm was developed to detect tamper events. Its results are detailed.

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Objective • Feasibility programme for on-board mass (OBM) monitoring of heavy vehicles (HVs) • Australian road authorities through Transport Certification Australia (TCA) • Accuracy of contemporary, commercially-available OBM units in Australia • Results need to be addressed/incorporated into specifications for Stage 2 of Intelligent Access Program (IAP) by Transport Certification Australia

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The idea of collective unintelligence is examined in this paper to highlight some of the conceptual and practical problems faced in modeling groups. Examples drawn from international crises and economics provide illustrative problems of collective failures to act in intelligent ways, despite the inputs and efforts of many skilled and intelligent parties. Choices made of “appropriate” perceptions, analysis and evaluations are examined along with how these might be combined. A simple vector representation illustrates some of the issues and creative possibilities in multi-party actions. Revealed as manifest (un-)intelligence are the resolutions of various problems and potentials that arise in dealing with the “each and all” of a group (wherein items are necessarily non-parallel and of unequal valency). Such issues challenge those seeking to model collective intelligence, but much may be learned.

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The advantages of a spherical imaging model are increasingly well recognized within the robotics community. Perhaps less well known is the use of the sphere for attitude estimation, control and scene structure estimation. This paper proposes the sphere as a unifying concept, not just for cameras, but for sensor fusion, estimation and control. We review and summarize relevant work in these areas and illustrate this with relevant simulation examples for spherical visual servoing and scene structure estimation.

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This paper describes technologies we have developed to perform autonomous large-scale off-world excavation. A scale dragline excavator of size similar to that required for lunar excavation was made capable of autonomous control. Systems have been put in place to allow remote operation of the machine from anywhere in the world. Algorithms have been developed for complete autonomous digging and dumping of material taking into account machine and terrain constraints and regolith variability. Experimental results are presented showing the ability to autonomously excavate and move large amounts of regolith and accurately place it at a specified location.

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This paper demonstrates some interesting connections between the hitherto disparate fields of mobile robot navigation and image-based visual servoing. A planar formulation of the well-known image-based visual servoing method leads to a bearing-only navigation system that requires no explicit localization and directly yields desired velocity. The well known benefits of image-based visual servoing such as robustness apply also to the planar case. Simulation results are presented.

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A virtual fence is created by applying an aversive stimulus to an animal when it approaches a predefined boundary. It is implemented by a small animal-borne computer system with a GPS receiver. This approach allows the implementation of virtual paddocks inside a normal physically-fenced paddock. Since the fence lines are virtual they can be moved by programming to meet the needs of animal or land management. This approach enables us to consider animals as agents with natural mobility that are controllable and to apply a vast body of theory in motion planning. In this paper we describe a herd-animal simulator and physical experiments conducted on a small herd of 10 animals using a Smart Collar. The Smart Collar consists of a GPS, PDA, wireless networking and a sound amplifier. We describe a motion planning algorithm that can move a virtual paddock subject to landscape constraints which is suitable for mustering cows. We present simulation results and data from experiments with 8 cows equipped with Smart Collars.

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If mobile robots are to perform useful tasks in the real-world they will require a catalog of fundamental navigation competencies and a means to select between them. In this paper we describe our work on strongly vision-based competencies: road-following, person or vehicle following, pose and position stabilization. Results from experiments on an outdoor autonomous tractor, a car-like vehicle, are presented.

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We consider multi-robot systems that include sensor nodes and aerial or ground robots networked together. We describe two cooperative algorithms that allow robots and sensors to enhance each other's performance. In the first algorithm, an aerial robot assists the localization of the sensors. In the second algorithm, a localized sensor network controls the navigation of an aerial robot. We present physical experiments with an flying robot and a large Mica Mote sensor network.

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This paper introduces the application of a sensor network to navigate a flying robot. We have developed distributed algorithms and efficient geographic routing techniques to incrementally guide one or more robots to points of interest based on sensor gradient fields, or along paths defined in terms of Cartesian coordinates. The robot itself is an integral part of the localization process which establishes the positions of sensors which are not known a priori. We use this system in a large-scale outdoor experiment with Mote sensors to guide an autonomous helicopter along a path encoded in the network. A simple handheld device, using this same environmental infrastructure, is used to guide humans.

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This paper demonstrates some interesting connections between the hitherto disparate fields of mobile robot navigation and image-based visual servoing. A planar formulation of the well-known image-based visual servoing method leads to a bearing-only navigation system that requires no explicit localization and directly yields desired velocity. The well known benefits of image-based visual servoing such as robustness apply also to the planar case. Simulation results are presented.