938 resultados para Ball-bearings.


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This thesis investigates the problem of robot navigation using only landmark bearings. The proposed system allows a robot to move to a ground target location specified by the sensor values observed at this ground target posi- tion. The control actions are computed based on the difference between the current landmark bearings and the target landmark bearings. No Cartesian coordinates with respect to the ground are computed by the control system. The robot navigates using solely information from the bearing sensor space. Most existing robot navigation systems require a ground frame (2D Cartesian coordinate system) in order to navigate from a ground point A to a ground point B. The commonly used sensors such as laser range scanner, sonar, infrared, and vision do not directly provide the 2D ground coordi- nates of the robot. The existing systems use the sensor measurements to localise the robot with respect to a map, a set of 2D coordinates of the objects of interest. It is more natural to navigate between the points in the sensor space corresponding to A and B without requiring the Cartesian map and the localisation process. Research on animals has revealed how insects are able to exploit very limited computational and memory resources to successfully navigate to a desired destination without computing Cartesian positions. For example, a honeybee balances the left and right optical flows to navigate in a nar- row corridor. Unlike many other ants, Cataglyphis bicolor does not secrete pheromone trails in order to find its way home but instead uses the sun as a compass to keep track of its home direction vector. The home vector can be inaccurate, so the ant also uses landmark recognition. More precisely, it takes snapshots and compass headings of some landmarks. To return home, the ant tries to line up the landmarks exactly as they were before it started wandering. This thesis introduces a navigation method based on reflex actions in sensor space. The sensor vector is made of the bearings of some landmarks, and the reflex action is a gradient descent with respect to the distance in sensor space between the current sensor vector and the target sensor vec- tor. Our theoretical analysis shows that except for some fully characterized pathological cases, any point is reachable from any other point by reflex action in the bearing sensor space provided the environment contains three landmarks and is free of obstacles. The trajectories of a robot using reflex navigation, like other image- based visual control strategies, do not correspond necessarily to the shortest paths on the ground, because the sensor error is minimized, not the moving distance on the ground. However, we show that the use of a sequence of waypoints in sensor space can address this problem. In order to identify relevant waypoints, we train a Self Organising Map (SOM) from a set of observations uniformly distributed with respect to the ground. This SOM provides a sense of location to the robot, and allows a form of path planning in sensor space. The navigation proposed system is analysed theoretically, and evaluated both in simulation and with experiments on a real robot.

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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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Intimate partner violence (IPV) is not only a problem for heterosexual couples. Although research in the area is beset by methodological and definitional problems, studies generally demonstrate that IPV also affects those who identify as non-heterosexual; that is, those sexualities that are typically categorized as lesbian, gay, bisexual, transgender, or intersex (LGBTI). IPV appears to be at least as prevalent in LGBTI relationships as it is in heterosexual couples, and follows similar patterns (e.g. Australian Research Centre on Sex, Health and Society 2006; Donovan et al. 2006; Chan 2005; Craft and Serovich 2005; Burke et al. 2002; Jeffries and Ball 2008; Kelly and Warshafsky 1987; Letellier 1994; Turrell 2000; Ristock 2003; Vickers 1996). There is, however, little in the way of specific community or social services support available to either victims or perpetrators of violence in same-sex relationships (see Vickers 1996). In addition, there are important differences in the experience of IPV between LGBTI and non-LGBTI victims, and even among LGBTI individuals; for example, among transgender populations (Chan 2005), and those who are HIV sero-positive (Craft and Serovich 2005). These different experiences of IPV include the use of HIV and the threat of “outing” a partner as tools of control, as just two examples (Jeffries and Ball 2008; Salyer 1999; WA Government 2008b). Such differences impact on how LGBTI victims respond to the violence, including whether or not and how they seek help, what services they are able to avail themselves of, and how likely they are to remain with, or return to, their violent partners (Burke et al. 2002). This chapter explores the prevalent heteronormative discourses that surround IPV, both within the academic literature, and in general social and government discourses. It seeks to understand how same-sex IPV remains largely invisible, and suggests that these dominant discourses play a major role in maintaining this invisibility. In many respects, it builds on work by a number of scholars who have begun to interrogate the criminal justice and social discourses surrounding violent crime, primarily sexual violence, and who problematize these discourses (see for example Carmody 2003; Carmody and Carrington 2000; Marcus 1992). It will begin by outlining these dominant discourses, and then problematize these by identifying some of the important differences between LGBTI IPV and IPV in heterosexual relationships. In doing so, this chapter will suggest some possible reasons for the silence regarding IPV in LGBTI relationships, and the effects that this can have on victims. Although an equally important area of research, and another point at which the limitations of dominant social discourses surrounding IPV can be brought to light, this chapter will not examine violence experienced by heterosexual men at the hands of their intimate female partners. Instead, it will restrict itself to IPV perpetrated within same-sex relationships.

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Heteronormative discourses provide the most common lens through which sexuality is understood within university curricula. This means that sexuality is discussed in terms of categories of identity, with heterosexuality accorded primacy and all ‘others’ indeed ‘othered.’ This paper reports on research carried out by the authors in a core first year university justice class, in which students of law and/or justice were required to engage with, discuss, and reflect on discourses on sexuality. It uses a poststructural framework to identify how students understand non-heterosexualities and how they personally relate to queer identities, in the sense that it asks questions about gender and sexual identity, and the discourses surrounding them. It was found that strongly negative attitudes to non-heterosexualities are quite resistant to challenge, and that some students express being confronted with queerness as a deep-seated fear of being drawn into otherness against their will. The result was that, while many students were able to unpack their attitudes towards queerness and engage in critical reflection and re-evaluation of their attitudes, students with strongly negative views towards non-heterosexualities conversely refused to engage at all, typically perceiving even the engagement itself as a threat to their core heterosexual identity. However, the authors caution against relying on the idea that students are simply “homophobic” to explain this reluctance, as this term does not necessarily account for the complexity of the discourses that inform students’ reactions in this context. This “homophobia” may simply be related to a way of performing gender and sexual identity as opposed to overt discrimination and fear.

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The social construction of sexuality over the past one hundred and fifty years has created a dichotomy between heterosexual and non-heterosexual identities that essentially positions the former as “normal” and the latter as deviant. Even Kinsey’s and others’ work on the continuum of sexualities did little to alter the predominantly heterosexist perception of the non-heterosexual as “other” (Kinsey, Pomeroy and Martin 2007; Esterberg 2006; Franceour and Noonan 2007). Some political action and academic work is beginning to challenge such perceptions. Even some avenues of social interaction, such as the recent proliferation of online communities, may also challenge such views, or at least contribute to their being rethought in some ways. This chapter explores a specific kind of online community devoted to fan fiction, specifically homoerotic – or what is known colloquially as “slash” – fan fiction. Fan fiction is fiction, published on the internet, and written by fans of well-known books and television shows, using the characters to create new and varied plots. “Slash” refers to the pairing of two of the male characters in a romantic relationship, and the term comes from the punctuation mark dividing the named pair as, for example, Spock/Kirk from the Star Trek television series. Although there are some slash fan-fiction stories devoted to female-female relationships – called “femmeslash” – the term “slash” generally refers to male-male relationships, and will be utilized throughout this chapter, given that the research discussed focuses on communities centered around one such male pairing.

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In Pollard v Trude [2008] QSC 119 (20 May 2008) the plaintiff claimed for personal injuries suffered when he was struck by a golf ball during the course of a tournament. The plaintiff was a member of a group of four, playing in a two-day tournament at Indooroopilly Golf Club. All four players had teed off at the second hole of the course and when the defendant took his second shot; his ball struck one of the trees bordering the fairway and deflected, hitting the plaintiff who was waiting to take his third stroke. As the ball was in flight, the defendant had called out "Watch out Errol", or words to that effect, to the plaintiff. The plaintiff suffered injury to his eye, leaving his vision impaired. The plaintiff sued in negligence, alleging that by failing to shout "fore" as is traditionally done in golf, the defendant had failed to warn the appellant and this was a breach of their duty. The claim in negligence was dismissed by the Queensland Supreme Court, holding that there had been no breach of the duty.

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This article discusses the design of a memorial space of the Tree of Knowledge, located in Oak Street, Barcaldine, Queensland designed by Brian Hooper Architect and M3 Architecture. Features of the design include the dead tree trunk underneath pieces of timber hanging down to show the original size of the tree in the 1890s and the root ball visible under a glass floor.

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This paper illustrates the prediction of opponent behaviour in a competitive, highly dynamic, multi-agent and partially observable environment, namely RoboCup small size league robot soccer. The performance is illustrated in the context of the highly successful robot soccer team, the RoboRoos. The project is broken into three tasks; classification of behaviours, modelling and prediction of behaviours and integration of the predictions into the existing planning system. A probabilistic approach is taken to dealing with the uncertainty in the observations and with representing the uncertainty in the prediction of the behaviours. Results are shown for a classification system using a Naïve Bayesian Network that determines the opponent’s current behaviour. These results are compared to an expert designed fuzzy behaviour classification system. The paper illustrates how the modelling system will use the information from behaviour classification to produce probability distributions that model the manner with which the opponents perform their behaviours. These probability distributions are show to match well with the existing multi-agent planning system (MAPS) that forms the core of the RoboRoos system.

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This paper describes the real time global vision system for the robot soccer team the RoboRoos. It has a highly optimised pipeline that includes thresholding, segmenting, colour normalising, object recognition and perspective and lens correction. It has a fast ‘paint’ colour calibration system that can calibrate in any face of the YUV or HSI cube. It also autonomously selects both an appropriate camera gain and colour gains robot regions across the field to achieve colour uniformity. Camera geometry calibration is performed automatically from selection of keypoints on the field. The system achieves a position accuracy of better than 15mm over a 4m × 5.5m field, and orientation accuracy to within 1°. It processes 614 × 480 pixels at 60Hz on a 2.0GHz Pentium 4 microprocessor.

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An adaptive agent improves its performance by learning from experience. This paper describes an approach to adaptation based on modelling dynamic elements of the environment in order to make predictions of likely future state. This approach is akin to an elite sports player being able to “read the play”, allowing for decisions to be made based on predictions of likely future outcomes. Modelling of the agent‟s likely future state is performed using Markov Chains and a technique called “Motion and Occupancy Grids”. The experiments in this paper compare the performance of the planning system with and without the use of this predictive model. The results of the study demonstrate a surprising decrease in performance when using the predictions of agent occupancy. The results are derived from statistical analysis of the agent‟s performance in a high fidelity simulation of a world leading real robot soccer team.

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This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup).

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Maintenance is a time consuming and expensive task for any golf course or driving range manager. For a golf course the primary tasks are grass mowing and maintenance (fertilizer and herbicide spreading), while for a driving range mowing, maintenance and ball collection are required. All these tasks require an operator to drive a vehicle along paths which are generally predefined. This paper presents some preliminary in-field tsting results for an automated tractor vehicle performing golf ball collection on an actual driving range, and mowing on difficult unstructured terrain.

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The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robots action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robots navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

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Deformation Behaviour of microcrystalline (mc) and nanocrystalline (nc) Mg-5%Al alloys produced by hot extrusion of ball-milled powders were investigated using instrumented indentation tests. The hardness values of the mc and nc metals exhibited indentation size effect (ISE), with nc alloys showing weaker ISE. The highly localized dislocation activities resulted in a small activation volume, hence enhanced strain rate sensitivity. Relative higher strain rate sensitivity and the negative Hall-Petch Relationship suggested the increasingly important role of grain boundary mediated mechanisms when the grain size decreased to nanometer region.