993 resultados para OBSTACLE AVOIDANCE PROCEDURES


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Jackson (2005) developed a hybrid model of personality and learning, known as the learning styles profiler (LSP) which was designed to span biological, socio-cognitive, and experiential research foci of personality and learning research. The hybrid model argues that functional and dysfunctional learning outcomes can be best understood in terms of how cognitions and experiences control, discipline, and re-express the biologically based scale of sensation-seeking. In two studies with part-time workers undertaking tertiary education (N equals 137 and 58), established models of approach and avoidance from each of the three different research foci were compared with Jackson's hybrid model in their predictiveness of leadership, work, and university outcomes using self-report and supervisor ratings. Results showed that the hybrid model was generally optimal and, as hypothesized, that goal orientation was a mediator of sensation-seeking on outcomes (work performance, university performance, leader behaviours, and counterproductive work behaviour). Our studies suggest that the hybrid model has considerable promise as a predictor of work and educational outcomes as well as dysfunctional outcomes.

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If there is a silver lining to the adversarial, dispute-prone nature of the building and construction industry, it can be found in the concomitant rise of innovative dispute resolution mechanisms. Time, cost and relationship concerns have meant that the formal adversarial system holds little appeal for disputing parties. As these alternative forms of dispute avoidance/resolution have matured in Australia over the last 20 years, attention has turned to the key characteristics of each process and their suitability to the building and construction industry. This article considers the role of dispute review boards (DRBs) and mediation as two alternative methods for avoiding/resolving disputes in the construction industry. Criteria are established for evaluating the efficacy of these procedures and their sensitivity to the needs of construction industry disputants. The ultimate conclusion reached is that DRBs represent a powerful, yet underutilised dispute resolution tool in Australia, and possess many industry-specific advantages that more traditional forms of alternative dispute resolution (particularly mediation) do not provide.

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In Bermingham v Priest [2002] QSC 057 jones J considered the position of persons seeking to claim damages where the Motor Accident Insurance Act 1994 applies prior to its amendment by the Motor Accident Insurance Amendment Act 2000, and where proceedings are brought close to expiration of the statutory limitation period.

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In JLG Industries Inc v Teetree Pty Ltd [2002] QDC 031 the court considered the implications in terms of costs of an offer to settle by the plaintiff under the UCPR where the element of compromise involved only acceptance of the amount of claim without interest.

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The decision of Chesterman J in Cross v Queensland Rugby Football Union Ltd [2001] QSC 173 (Supreme Court of Queensland, No 3426 of 1997), Chesterman J, 30.5.2001) opens the possibilities for delivering interrogatories, particularly in the context of interrogatories relating to an opponent's version of events.

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This article explains the new pre-court procedures and additional procedures designed to foster settlement of claims introduced by the Workcover Queensland Act 1996, and the implication of the new provisions for practitioners.

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Highway construction projects have direct impacts on adjacent businesses. The nature and the degree of impact depend on individual business characterization and project specific factors. The type of business is also a relevant factor in predicting the impact of transportation construction projects. This paper presents the results of research focused on developing an in-depth understanding of these relationships. The study includes project case studies of three transportation construction projects in Florida. Surveys were conducted with all adjacent businesses, which were combined with analyses of the business accommodation procedures employed by State Highway Agencies (SHAs) nationwide to provide measure the efficiency of present rules. The results include an analysis of differing priorities for different classification of businesses and development of design and construction management best practices to better accommodate businesses during highway construction. A pilot project that employed business accommodation principles devised in this research, and improvements to business accommodations observed were compared to cases where no measures were taken.

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This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.

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This thesis examines perceptions of advertising on social networking sites (SNS), in particular consumers' privacy concerns, advertising engagement and advertising avoidance. It contributes to the understanding of social media by providing results of a longitudinal investigation of consumer perceptions of advertising, a topography of engagement and avoidance triggers and a three dimensional model of advertising avoidance on SNS. This research used a mixed methodology, employing Critical Incident Technique, In-depth interviews and online surveys.

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Evolutionary algorithms are playing an increasingly important role as search methods in cognitive science domains. In this study, methodological issues in the use of evolutionary algorithms were investigated via simulations in which procedures were systematically varied to modify the selection pressures on populations of evolving agents. Traditional roulette wheel, tournament, and variations of these selection algorithms were compared on the “needle-in-a-haystack” problem developed by Hinton and Nowlan in their 1987 study of the Baldwin effect. The task is an important one for cognitive science, as it demonstrates the power of learning as a local search technique in smoothing a fitness landscape that lacks gradient information. One aspect that has continued to foster interest in the problem is the observation of residual learning ability in simulated populations even after long periods of time. Effective evolutionary algorithms balance their search effort between broad exploration of the search space and in-depth exploitation of promising solutions already found. Issues discussed include the differential effects of rank and proportional selection, the tradeoff between migration of populations towards good solutions and maintenance of diversity, and the development of measures that illustrate how each selection algorithm affects the search process over generations. We show that both roulette wheel and tournament algorithms can be modified to appropriately balance search between exploration and exploitation, and effectively eliminate residual learning in this problem.

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This thesis presents a new vision-based decision and control strategy for automated aircraft collision avoidance that can be realistically applied to the See and Avoid problem. The effectiveness of the control strategy positions the research as a major contribution toward realising the simultaneous operation of manned and unmanned aircraft within civilian airspace. Key developments include novel classical and visual predictive control frameworks, and a performance evaluation technique aligned with existing aviation practise and applicable to autonomous systems. The overall approach is demonstrated through experimental results on a small multirotor unmanned aircraft, and through high fidelity probabilistic simulation studies.

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This invention concerns the control of rotating excavation machinery, for instance to avoid collisions with obstacles. In a first aspect the invention is a control system for autonomous path planning in excavation machinery, comprising: A map generation subsystem to receive data from an array of disparate and complementary sensors to generate a 3-Dimensional digital terrain and obstacle map referenced to a coordinate frame related to the machine's geometry, during normal operation of the machine. An obstacle detection subsystem to find and identify obstacles in the digital terrain and obstacle map, and then to refine the map by identifying exclusion zones that are within reach of the machine during operation. A collision detection subsystem that uses knowledge of the machine's position and movements, as well as the digital terrain and obstacle map, to identify and predict possible collisions with itself or other obstacles, and then uses a forward motion planner to predict collisions in a planned path. And, a path planning subsystem that uses information from the other subsystems to vary planned paths to avoid obstacles and collisions. In other aspects the invention is excavation machinery including the control system; a method for control of excavation machinery; and firmware and software versions of the control system.

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We propose a system incorporating a tight integration between computer vision and robot control modules on a complex, high-DOF humanoid robot. Its functionality is showcased by having our iCub humanoid robot pick-up objects from a table in front of it. An important feature is that the system can avoid obstacles - other objects detected in the visual stream - while reaching for the intended target object. Our integration also allows for non-static environments, i.e. the reaching is adapted on-the-fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. Furthermore we show that this system can be used both in autonomous and tele-operation scenarios.