206 resultados para Path Planning Under Uncertainty
Resumo:
What type of probability theory best describes the way humans make judgments under uncertainty and decisions under conflict? Although rational models of cognition have become prominent and have achieved much success, they adhere to the laws of classical probability theory despite the fact that human reasoning does not always conform to these laws. For this reason we have seen the recent emergence of models based on an alternative probabilistic framework drawn from quantum theory. These quantum models show promise in addressing cognitive phenomena that have proven recalcitrant to modeling by means of classical probability theory. This review compares and contrasts probabilistic models based on Bayesian or classical versus quantum principles, and highlights the advantages and disadvantages of each approach.
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This thesis explored the impact of non-contractual agreements in economic decisions. These statements of intent serve as a commitment device in strategic decisions and have been found to be an effective alternative to strong regulations in promoting social behaviour. Three studies have been undertaken using conceptual and methodological approaches from Behavioral and Experimental Economics. The first study explored in a public good setting the effect of public statements about intended social behaviour. The second study tested whether promises can help to promote co-operation in environments with uncertain choice options. The third study investigated a possible application of statement of intent and tested the effect of payment promises in a tax setting.
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A key component of robotic path planning is ensuring that one can reliably navigate a vehicle to a desired location. In addition, when the features of interest are dynamic and move with oceanic currents, vehicle speed plays an important role in the planning exercise to ensure that vehicles are in the right place at the right time. Aquatic robot design is moving towards utilizing the environment for propulsion rather than traditional motors and propellers. These new vehicles are able to realize significantly increased endurance, however the mission planning problem, in turn, becomes more difficult as the vehicle velocity is not directly controllable. In this paper, we examine Gaussian process models applied to existing wave model data to predict the behavior, i.e., velocity, of a Wave Glider Autonomous Surface Vehicle. Using training data from an on-board sensor and forecasting with the WAVEWATCH III model, our probabilistic regression models created an effective method for forecasting WG velocity.
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The world is rich with information such as signage and maps to assist humans to navigate. We present a method to extract topological spatial information from a generic bitmap floor plan and build a topometric graph that can be used by a mobile robot for tasks such as path planning and guided exploration. The algorithm first detects and extracts text in an image of the floor plan. Using the locations of the extracted text, flood fill is used to find the rooms and hallways. Doors are found by matching SURF features and these form the connections between rooms, which are the edges of the topological graph. Our system is able to automatically detect doors and differentiate between hallways and rooms, which is important for effective navigation. We show that our method can extract a topometric graph from a floor plan and is robust against ambiguous cases most commonly seen in floor plans including elevators and stairwells.
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This report describes the development and simulation of a variable rate controller for a 6-degree of freedom nonlinear model. The variable rate simulation model represents an off the shelf autopilot. Flight experiment involves risks and can be expensive. Therefore a dynamic model to understand the performance characteristics of the UAS in mission simulation before actual flight test or to obtain parameters needed for the flight is important. The control and guidance is implemented in Simulink. The report tests the use of the model for air search and air sampling path planning. A GUI in which a set of mission scenarios, in which two experts (mission expert, i.e. air sampling or air search and an UAV expert) interact, is presented showing the benefits of the method.
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This research deals with the development of a Solar-Powered UAV designed for remote sensing, in particular to the development of the autopilot sub-system and path planning. The design of the Solar-Powered UAS followed a systems engineering methodology, by first defining system architecture, and selecting each subsystem. Validation tests and integration of autopilot is performed, in order to evaluate the performances of each subsystem and to obtain a global operational system for data collection missions. The flight tests planning and simulation results are also explored in order to verify the mission capabilities using an autopilot on a UAS. The important aspect of this research is to develop a Solar-Powered UAS for the purpose of data collection and video monitoring, especially data and images from the ground; transmit to the GS (Ground Station), segment the collected data, and afterwards analyze it with a Matlab code.
Resumo:
Robotic vision is limited by line of sight and onboard camera capabilities. Robots can acquire video or images from remote cameras, but processing additional data has a computational burden. This paper applies the Distributed Robotic Vision Service, DRVS, to robot path planning using data outside line-of-sight of the robot. DRVS implements a distributed visual object detection service to distributes the computation to remote camera nodes with processing capabilities. Robots request task-specific object detection from DRVS by specifying a geographic region of interest and object type. The remote camera nodes perform the visual processing and send the high-level object information to the robot. Additionally, DRVS relieves robots of sensor discovery by dynamically distributing object detection requests to remote camera nodes. Tested over two different indoor path planning tasks DRVS showed dramatic reduction in mobile robot compute load and wireless network utilization.
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Risks and uncertainties are inevitable in engineering projects and infrastructure investments. Decisions about investment in infrastructure such as for maintenance, rehabilitation and construction works can pose risks, and may generate significant impacts on social, cultural, environmental and other related issues. This report presents the results of a literature review of current practice in identifying, quantifying and managing risks and predicting impacts as part of the planning and assessment process for infrastructure investment proposals. In assessing proposals for investment in infrastructure, it is necessary to consider social, cultural and environmental risks and impacts to the overall community, as well as financial risks to the investor. The report defines and explains the concept of risk and uncertainty, and describes the three main methodology approaches to the analysis of risk and uncertainty in investment planning for infrastructure, viz examining a range of scenarios or options, sensitivity analysis, and a statistical probability approach, listed here in order of increasing merit and complexity. Forecasts of costs, benefits and community impacts of infrastructure are recognised as central aspects of developing and assessing investment proposals. Increasingly complex modelling techniques are being used for investment evaluation. The literature review identified forecasting errors as the major cause of risk. The report contains a summary of the broad nature of decision-making tools used by governments and other organisations in Australia, New Zealand, Europe and North America, and shows their overall approach to risk assessment in assessing public infrastructure proposals. While there are established techniques to quantify financial and economic risks, quantification is far less developed for political, social and environmental risks and impacts. The report contains a summary of the broad nature of decision-making tools used by governments and other organisations in Australia, New Zealand, Europe and North America, and shows their overall approach to risk assessment in assessing public infrastructure proposals. While there are established techniques to quantify financial and economic risks, quantification is far less developed for political, social and environmental risks and impacts. For risks that cannot be readily quantified, assessment techniques commonly include classification or rating systems for likelihood and consequence. The report outlines the system used by the Australian Defence Organisation and in the Australian Standard on risk management. After each risk is identified and quantified or rated, consideration can be given to reducing the risk, and managing any remaining risk as part of the scope of the project. The literature review identified use of risk mapping techniques by a North American chemical company and by the Australian Defence Organisation. This literature review has enabled a risk assessment strategy to be developed, and will underpin an examination of the feasibility of developing a risk assessment capability using a probability approach.
Resumo:
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.
Resumo:
A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.
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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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The Western Downs region, located in Southern Queensland, about 200 kilometres west of Brisbane, has been experiencing rapid and significant changes over the past years, due to a massive boom in the energy sector. The rapid growth triggered by the development of mining and energy sectors has generated environmental, socio-economic and land use issues, and has revealed strong weaknesses within the region’s current governance arrangements. The present paper develops a four-stage approach to managing current and expected changes in a resource-based region under tremendous stress and uncertainty.
Resumo:
Performance based planning is a form of planning regulation that is not well understood and the theoretical advantages of this type of planning are rarely achieved in practice. Normatively, this type of regulation relies on performance standards that are quantifiable and technically based which are designed to manage the effects of development, where performance standards provide certainty in respect of the level of performance and the means of achievement is flexible. Few empirical studies have attempted to examine how performance based planning has been conceptualised and implemented in practice. Existing literature is predominately anecdotal and consultant based (Baker et al. 2006) and has not sought to quantitatively examine how land use has been managed or determine how context influences implementation. The Integrated Planning Act 1997 (IPA) operated as Queensland’s principal planning legislation between March 1998 and December 2009. The IPA prevented Local Governments from prohibiting development or use and the term zone was absent from the legislation. While the IPA did not use the term performance based planning, the system is widely considered to be performance based in practice (e.g. Baker et al. 2006; Steele 2009a, 2009b). However, the degree to which the IPA and the planning system in Queensland is performance based is debated (e.g. Yearbury 1998; England 2004). Four research questions guided the research framework using Queensland as the case study. The questions sought to: determine if there is a common understanding of performance based planning; identify how performance based planning was expressed under the IPA; understand how performance based planning was implemented in plans; and explore the experiences of participants in the planning system. The research developed a performance adoption spectrum. The spectrum describes how performance based planning is implemented, ranging between pure and hybrid interpretations. An ex-post evaluation of seventeen IPA plans sought to determine plan performativity within the conceptual spectrum. Land use was examined from the procedural dimension of performance (Assessment Tables) and the substantive dimension of performance (Codes). A documentary analysis and forty one interviews supplemented the research. The analytical framework considered how context influenced performance based planning, including whether: the location of the local government affected land use management techniques; temporal variation in implementation exists; plan-making guidelines affected implementation; different perceptions of the concept exist; this type of planning applies to a range of spatial scales. Outcomes were viewed as the medium for determining the acceptability of development in Queensland, a significant departure from pure approaches found in the United States. Interviews highlighted the absence of plan-making direction in the IPA, which contributed to the confusion about the intended direction of the planning system and the myth that the IPA would guarantee a performance based system. A hybridised form of performance based planning evolved in Queensland which was dependent on prescriptive land use zones and specification of land use type, with some local governments going to extreme lengths to discourage certain activities in a predetermined manner. Context had varying degrees of influence on plan-making methods. Decision-making was found to be inconsistent and the system created a range of unforeseen consequences including difficulties associated with land valuation, increased development speculation, and the role of planners in court was found to be less critical than in the previous planning system.
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This paper presents the Mossman Mill District Practices Framework. It was developed in the Wet Tropics region within the Great Barrier Reef in north-eastern Australia to describe the environmental benefits of agricultural management practices for the sugar cane industry. The framework translates complex, unclear and overlapping environmental plans, policy and legal arrangements into a simple framework of management practices that landholders can use to improve their management actions. Practices range from those that are old or outdated through to aspirational practices that have the potential to achieve desired resource condition targets. The framework has been applied by stakeholders at multiple scales to better coordinate and integrate a range of policy arrangements to improve natural resource management. It has been used to structure monitoring and evaluation in order to underpin a more adaptive approach to planning at mill district and property scale. Potentially, the framework and approach can be applied across fields of planning where adaptive management is needed. It has the potential to overcome many of the criticisms of property-scale and regional Natural Resource Management.