110 resultados para Optimum-path forests


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In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

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Exploiting wind-energy is one possible way to ex- tend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

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The study of criminal career paths is necessary to understand the methods of success employed by high-performing criminals. The aim of this article is to focus on the career path of Jack Herbert who set up and maintained extensive corruption networks between organised crime groups and police in the Australian state of Queensland. This study builds on Morselli’s work on the career paths of Sammy Gravano and Howard Marks that demonstrate how understanding social networks is an essential part of comprehending how organised criminals succeed. The data for this study were taken from the transcripts of the Fitzgerald Commission of Inquiry, which uncovered the extensive and resilient corruption network operated by Herbert. Herbert’s relationships have been plotted to establish the nature of his operations. The findings indicate that communication of trust both allows for success and sets the boundaries of a network. Most importantly, this case study identifies Herbert’s reliance on holding a monopoly as the cornerstone of his network power and position. This article adds to the literature on criminal career paths by moving away from a classic organised criminal grouping into the area of police corruption and uncovers the distinctive opportunities that this position offers the career criminal.

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Our Counselling and ISS team organised, in early December, 2011 a celebration of two years of art workshops and activities provided for our University post-graduate research students. The workshops had a number of benefits. They were to raise awareness of biodiversity and forests as well as providing a forum for engaging with others and an opportunity to belong to a semi-regular group. The 2010 theme had been the United Nations International Year of Biodiversity and the 2011 theme had been the United Nations International Year of Forests.

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Our Counselling and ISS team organised, in early December, 2011 a celebration of two years of art workshops and activities provided for our University post-graduate research students. The workshops had a number of benefits. They were to raise awareness of biodiversity and forests as well as providing a forum for engaging with others and an opportunity to belong to a semi-regular group. The 2010 theme had been the United Nations International Year of Biodiversity and the 2011 theme had been the United Nations International Year of Forests.

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Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

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Spatial navigation requires the processing of complex, disparate and often ambiguous sensory data. The neurocomputations underpinning this vital ability remain poorly understood. Controversy remains as to whether multimodal sensory information must be combined into a unified representation, consistent with Tolman's "cognitive map", or whether differential activation of independent navigation modules suffice to explain observed navigation behaviour. Here we demonstrate that key neural correlates of spatial navigation in darkness cannot be explained if the path integration system acted independently of boundary (landmark) information. In vivo recordings demonstrate that the rodent head direction (HD) system becomes unstable within three minutes without vision. In contrast, rodents maintain stable place fields and grid fields for over half an hour without vision. Using a simple HD error model, we show analytically that idiothetic path integration (iPI) alone cannot be used to maintain any stable place representation beyond two to three minutes. We then use a measure of place stability based on information theoretic principles to prove that featureless boundaries alone cannot be used to improve localization above chance level. Having shown that neither iPI nor boundaries alone are sufficient, we then address the question of whether their combination is sufficient and - we conjecture - necessary to maintain place stability for prolonged periods without vision. We addressed this question in simulations and robot experiments using a navigation model comprising of a particle filter and boundary map. The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. We discuss our findings in light of current theories of animal navigation and neuronal computation, and elaborate on their implications and significance for the design, analysis and interpretation of experiments.

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Vehicular Ad-hoc Networks (VANET) have different characteristics compared to other mobile ad-hoc networks. The dynamic nature of the vehicles which act as routers and clients are connected with unreliable radio links and Routing becomes a complex problem. First we propose CO-GPSR (Cooperative GPSR), an extension of the traditional GPSR (Greedy Perimeter Stateless Routing) which uses relay nodes which exploit radio path diversity in a vehicular network to increase routing performance. Next we formulate a Multi-objective decision making problem to select optimum packet relaying nodes to increase the routing performance further. We use cross layer information for the optimization process. We evaluate the routing performance more comprehensively using realistic vehicular traces and a Nakagami fading propagation model optimized for highway scenarios in VANETs. Our results show that when Multi-objective decision making is used for cross layer optimization of routing a 70% performance increment can be obtained for low vehicle densities on average, which is a two fold increase compared to the single criteria maximization approach.

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Problems with charity law jurisprudence persist. The difficulties arose in the 20th century and are fundamental to the way the doctrine is presently theorised. They grew out of the approach taken in Pemsel’s Case to the categorisation of the ‘spirit and intendment’ of the Preamble to the Statute of Charitable Uses. Recent statutory reforms, such as the Charities Act 2006 (Eng&W), have compounded the underlying problems rather than resolving them. This paper aims to stimulate thinking about a new foundation for charity jurisprudence – while the approach may seem radical, the paper argues that these new foundations can be discerned underlying the current jurisprudence. The difficulties can be overcome by rediscovering the underlying jurisprudence which is disregarded in the current approach to categorisation. Giving voice, in contemporary language, to that foundational jurisprudence, this paper provides a way out of the current problems. It also provides an alternative way of conceptualising the doctrine of charitable purpose to guide reform.

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The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. The goal of this work is then to develop a Multi-Objective (MO) optimisation tool able to provide a set of optimal solutions for the inspection task, given the environment data, the mission requirements and the definition of the objectives to minimise. Results indicate the robustness and capability of the method to find the trade-off between the Pareto-optimal solutions.

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This paper presents a novel evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles (UAVs) with tactical and kinematic constraints. A genetic algorithm (GA) is modified and extended for path planning. Two GAs are seeded at the initial and final positions with a common objective to minimise their distance apart under given UAV constraints. This is accomplished by the synchronous optimisation of subsequent control vectors. The proposed evolutionary computation approach is called synchronous genetic algorithm (SGA). The sequence of control vectors generated by the SGA constitutes to a near-optimal path plan. The resulting path plan exhibits no discontinuity when transitioning from curve to straight trajectories. Experiments and results show that the paths generated by the SGA are within 2% of the optimal solution. Such a path planner when implemented on a hardware accelerator, such as field programmable gate array chips, can be used in the UAV as on-board replanner, as well as in ground station systems for assisting in high precision planning and modelling of mission scenarios.

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Ocean gliders constitute an important advance in the highly demanding ocean monitoring scenario. Their effciency, endurance and increasing robustness make these vehicles an ideal observing platform for many long term oceanographic applications. However, they have proved to be also useful in the opportunis-tic short term characterization of dynamic structures. Among these, mesoscale eddies are of particular interest due to the relevance they have in many oceano-graphic processes.

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Through a forest inventory in parts of the Amudarya river delta, Central Asia, we assessed the impact of ongoing forest degradation on the emissions of greenhouse gases (GHG) from soils. Interpretation of aerial photographs from 2001, combined with data on forest inventory in 1990 and field survey in 2003 provided comprehensive information about the extent and changes of the natural tugai riparian forests and tree plantations in the delta. The findings show an average annual deforestation rate of almost 1.3% and an even higher rate of land use change from tugai forests to land with only sparse tree cover. These annual rates of deforestation and forest degradation are higher than the global annual forest loss. By 2003, the tugai forest area had drastically decreased to about 60% compared to an inventory in 1990. Significant differences in soil GHG emissions between forest and agricultural land use underscore the impact of the ongoing land use change on the emission of soil-borne GHGs. The conversion of tugai forests into irrigated croplands will release 2.5 t CO2 equivalents per hectare per year due to elevated emissions of N2O and CH4. This demonstrates that the ongoing transformation of tugai forests into agricultural land-use systems did not only lead to a loss of biodiversity and of a unique ecosystem, but substantially impacts the biosphere-atmosphere exchange of GHG and soil C and N turnover processes.

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Forest regulation is never far from the headlines. The recent COP 18 negotiations held in Doha towards the end of 2012 were criticized by observers for slowing the development of the ‘REDD+’ initiative and for marking the end of ‘Forest Day’, whilst in the last month controversy has arisen following reports that the World Bank’s investment in forestry-related projects has failed to address poverty or benefit local communities. Dr Rowena Maguire’s research focuses on international climate and forest regulation and indigenous and community groups rights and responsibilities in connection with environmental management. Her new book, Global Forest Governance, identifies the fundamental legal principles and governance requirements of Sustainable Forest Management, an introduction to which is provided in her article below.