623 resultados para Motion path planning
Resumo:
Queensland's new State Planning Policy for Coastal Protection, released in March and approved in April 2011 as part of the Queensland Coastal Plan, stipulates that local governments prepare and implement adaptation strategies for built up areas projected to be subject to coastal hazards between present day and 2100. Urban localities within the delineated coastal high hazard zone (as determined by models incorporating a 0.8 meter rise in sea level and a 10% increase in the maximum cyclone activity) will be required to re-evaluate their plans to accommodate growth, revising land use plans to minimise impacts of anticipated erosion and flooding on developed areas and infrastructure. While implementation of such strategies would aid in avoidance or minimisation of risk exposure, communities are likely to face significant challenges in such implementation, especially as development in Queensland is so intensely focussed upon its coasts with these new policies directing development away from highly desirable waterfront land. This paper examines models of planning theory to understand how we plan when faced with technically complex problems towards formulation of a framework for evaluating and improving practice.
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This paper is about planning paths from overhead imagery, the novelty of which is taking explicit account of uncertainty in terrain classification and spatial variation in terrain cost. The image is first classified using a multi-class Gaussian Process Classifier which provides probabilities of class membership at each location in the image. The probability of class membership at a particular grid location is then combined with a terrain cost evaluated at that location using a spatial Gaussian process. The resulting cost function is, in turn, passed to a planner. This allows both the uncertainty in terrain classification and spatial variations in terrain costs to be incorporated into the planned path. Because the cost of traversing a grid cell is now a probability density rather than a single scalar value, we can produce not only the most-likely shortest path between points on the map, but also sample from the cost map to produce a distribution of paths between the points. Results are shown in the form of planned paths over aerial maps, these paths are shown to vary in response to local variations in terrain cost.
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Organ motion as a result of respiration is an important field of research for medical physics. Knowledge of magnitude and direction of this motion is necessary to allow for more accurate radiotherapy treatment planning. This will result in higher doses to the tumour whilst sparing healthy tissue. This project involved human trials, where the radiation therapy patient's kidneys were CT scanned under three different conditions; whilst free breathing (FB), breath-hold at normal tidal inspiration (BHIN), and breath-hold at normal tidal expiration (BHEX). The magnitude of motion was measured by recording the outline of the kidney from a Beam's Eye View (BEV). The centre of mass of this 2D shape was calculated for each set using "ImageJ" software and the magnitude of movement determined from the change in the centroid's coordinates between the BHIN and BHEX scans. The movement ranged from, for the left and right kidneys, 4-46mm and 2-44mm in the superior/inferior (axial) plane, 1-21mm and 2- 16mm in the anterior/posterior (coronal) plane, and 0-6mm and 0-8mm in the lateral/medial (sagittal) plane. From exhale to inhale, the kidneys tended to move inferiorly, anteriorly and laterally. A standard radiotherapy plan, designed to treat the para-aortics with opposed lateral fields was performed on the free breathing (planning) CT set. The field size and arrangement was set up using the same parameters for each subject. The prescription was to deliver 45 Gray in 25 fractions. This field arrangement and prescription was then copied over to the breath hold CT sets, and the dosimetric differences were compared using Dose Volume Histograms (DVH). The point of comparison for the three sets was recorded as the percentage volume of kidney receiving less than or equal to 10 Gray. The QUASAR respiratory motion phantom was used with the range of motion determined from the human study. The phantom was imaged, planned and treated with a linear accelerator with dose determined by film. The effect of the motion was measured by the change in the penumbra of the film and compared to the penumbra from the treatment planning system.
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Path integration is a process in which observers derive their location by integrating self-motion signals along their locomotion trajectory. Although the medial temporal lobe (MTL) is thought to take part in path integration, the scope of its role for path integration remains unclear. To address this issue, we administered a variety of tasks involving path integration and other related processes to a group of neurosurgical patients whose MTL was unilaterally resected as therapy for epilepsy. These patients were unimpaired relative to neurologically intact controls in many tasks that required integration of various kinds of sensory self-motion information. However, the same patients (especially those who had lesions in the right hemisphere) walked farther than the controls when attempting to walk without vision to a previewed target. Importantly, this task was unique in our test battery in that it allowed participants to form a mental representation of the target location and anticipate their upcoming walking trajectory before they began moving. Thus, these results put forth a new idea that the role of MTL structures for human path integration may stem from their participation in predicting the consequences of one's locomotor actions. The strengths of this new theoretical viewpoint are discussed.
Learned stochastic mobility prediction for planning with control uncertainty on unstructured terrain
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Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This mobility prediction model is trained using sample executions of motion primitives on representative terrain, and predicts the future outcome of control actions on similar terrain. Using Gaussian process regression allows us to exploit its inherent measure of prediction uncertainty in planning. We integrate mobility prediction into a Markov decision process framework and use dynamic programming to construct a control policy for navigation to a goal region in a terrain map built using an on-board depth sensor. We consider both rigid terrain, consisting of uneven ground, small rocks, and non-traversable rocks, and also deformable terrain. We introduce two methods for training the mobility prediction model from either proprioceptive or exteroceptive observations, and report results from nearly 300 experimental trials using a planetary rover platform in a Mars-analogue environment. Our results validate the approach and demonstrate the value of planning under uncertainty for safe and reliable navigation.
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Path integration is a process with which navigators derive their current position and orientation by integrating self-motion signals along a locomotion trajectory. It has been suggested that path integration becomes disproportionately erroneous when the trajectory crosses itself. However, there is a possibility that this previous finding was confounded by effects of the length of a traveled path and the amount of turns experienced along the path, two factors that are known to affect path integration performance. The present study was designed to investigate whether the crossover of a locomotion trajectory truly increases errors of path integration. In an experiment, blindfolded human navigators were guided along four paths that varied in their lengths and turns, and attempted to walk directly back to the beginning of the paths. Only one of the four paths contained a crossover. Results showed that errors yielded from the path containing the crossover were not always larger than those observed in other paths, and the errors were attributed solely to the effects of longer path lengths or greater degrees of turns. These results demonstrated that path crossover does not always cause significant disruption in path integration processes. Implications of the present findings for models of path integration are discussed.
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There is growing interest in the biomechanics of ‘fusionless’ implant constructs used for deformity correction in the thoracic spine, however, there are questions over the comparability of in vitro biomechanical studies from different research groups due to the various methods used for specimen preparation, testing and data collection. The aim of this study was to identify the effect of two key factors on the stiffness of immature bovine thoracic spine motion segments: (i) repeated cyclic loading and (ii) multiple freeze-thaw cycles, to aid in the planning and interpretation of in vitro studies. Two groups of thoracic spine motion segments from 6-8 week old calves were tested in flexion/extension, right/left lateral bending, and right/left axial rotation under moment control. Group (A) were tested with continuous repeated cyclic loading for 500 cycles with data recorded at cycles 3, 5, 10, 25, 50, 100, 200, 300, 400 and 500. Group (B) were tested after each of five freeze-thaw sequences, with data collected from the 10th load cycle in each sequence. Group A: Flexion/extension stiffness reduced significantly over the 500 load cycles (-22%; P=0.001), but there was no significant change between the 5th and 200th load cycles. Lateral bending stiffness decreased significantly (-18%; P=0.009) over the 500 load cycles, but there was no significant change in axial rotation stiffness (P=0.137). Group B: There was no significant difference between mean stiffness over the five freeze-thaw sequences in flexion/extension (P=0.813) and a near significant reduction in mean stiffness in axial rotation (-6%; P=0.07). However, there was a statistically significant increase in stiffness in lateral bending (+30%; P=0.007). Comparison of in vitro testing results for immature thoracic bovine spine segments between studies can be performed with up to 200 load cycles without significant changes in stiffness. However, when testing protocols require greater than 200 cycles, or when repeated freeze-thaw cycles are involved, it is important to account for the effect of cumulative load and freeze-thaw cycles on spine segment stiffness.
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A curvilinear thin film model is used to simulate the motion of droplets on a virtual leaf surface, with a view to better understand the retention of agricultural sprays on plants. The governing model, adapted from Roy et al. (2002 J. Fluid Mech. 454, 235–261) with the addition of a disjoining pressure term, describes the gravity- and curvature driven flow of a small droplet on a complex substrate: a cotton leaf reconstructed from digitized scan data. Coalescence is the key mechanism behind spray coating of foliage, and our simulations demonstrate that various experimentally observed coalescence behaviours can be reproduced qualitatively. By varying the contact angle over the domain, we also demonstrate that the presence of a chemical defect can act as an obstacle to the droplet’s path, causing break-up. In simulations on the virtual leaf, it is found that the movement of a typical spray size droplet is driven almost exclusively by substrate curvature gradients. It is not until droplet mass is sufficiently increased via coalescence that gravity becomes the dominating force.
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Purpose Traditional construction planning relies upon the critical path method (CPM) and bar charts. Both of these methods suffer from visualization and timing issues that could be addressed by 4D technology specifically geared to meet the needs of the construction industry. This paper proposed a new construction planning approach based on simulation by using a game engine. Design/methodology/approach A 4D automatic simulation tool was developed and a case study was carried out. The proposed tool was used to simulate and optimize the plans for the installation of a temporary platform for piling in a civil construction project in Hong Kong. The tool simulated the result of the construction process with three variables: 1) equipment, 2) site layout and 3) schedule. Through this, the construction team was able to repeatedly simulate a range of options. Findings The results indicate that the proposed approach can provide a user-friendly 4D simulation platform for the construction industry. The simulation can also identify the solution being sought by the construction team. The paper also identifies directions for further development of the 4D technology as an aid in construction planning and decision-making. Research limitations/implications The tests on the tool are limited to a single case study and further research is needed to test the use of game engines for construction planning in different construction projects to verify its effectiveness. Future research could also explore the use of alternative game engines and compare their performance and results. Originality/value The authors proposed the use of game engine to simulate the construction process based on resources, working space and construction schedule. The developed tool can be used by end-users without simulation experience.
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Construction industry contributes significantly to environmental degradation, and governments in many countries which are endeavouring to address the situation. Malaysia is no exception. This paper examines the path towards green construction project delivery in Malaysia, focusing on current green policies and initiatives by governments. The historical waves in Malaysian approaches to tackling environmental issues are described, starting from the early 20th century, through the 1990s to the present, and the influence of these approaches on construction practices is analysed. Based on the findings of policy review, essential green construction practices aimed at mitigating the adverse effects of construction activities on the environment in Malaysia were identified. This paper paves the way for future studies in construction and sustainability in Malaysia, especially for the Southeast Asian region where sustainability practices are urgently needed.
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In this paper, we introduce a path algebra well suited for navigation in environments that can be abstracted as topological graphs. From this path algebra, we derive algorithms to reduce routes in such environments. The routes are reduced in the sense that they are shorter (contain fewer edges), but still connect the endpoints of the initial routes. Contrary to planning methods descended from Disjktra’s Shortest Path Algorithm like D , the navigation methods derived from our path algebra do not require any graph representation. We prove that the reduced routes are optimal when the graphs are without cycles. In the case of graphs with cycles, we prove that whatever the length of the initial route, the length of the reduced route is bounded by a constant that only depends on the structure of the environment.
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Recent decades have seen an almost obsessive focus on creativity in an urban development context. Yet, creativity has come to be prized not so much for the intrinsic values of imagination, innovation and experimentation as for the possibility to exploit these qualities as a means of urban revitalization and wealth generation. This policy emphasis has both contributed to the misplaced assumption that artistic activity causes gentrification and displacement while, at the same time, often setting in motion programs that are detrimental to the creative environments such policies claim to support. It is time to end the current approach to creative city planning, which treats the arts as amenities to catalyze land development and lure upscale consumption.
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There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.