824 resultados para Robot autonomy


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As Australian society 1s agemg, individuals are increasingly concerned about managing their future, including making decisions about the medical treatment they may wish to receive or refuse if they lose decision-making capacity. To date, there has been relatively little research into the extent to which legal regulation allows competent adults to make advance refusals of life-sustaining medical treatment that will bind health professionals and others when a decision needs to be made at a future time. This thesis aims to fill this gap in the research by presenting the results of research into the legal regulation of advance directives that refuse life-sustaining medical treatment. In the five papers that comprise this thesis, the law that governs this area is examined, and the ethical principle of autonomy is used to critically evaluate that law. The principal finding of this research is that the current scheme of regulation is ineffective to adequately promote the right of a competent adult to make binding advance directives about refusal of medical treatment. The research concludes that legislation should be enacted to enable individuals to complete an advance directive, only imposing restrictions to the extent that this is necessary to promote individual autonomy. The thesis first examines the principle of autonomy upon which the common law (and some statutory law) is expressed to be based, to determine whether that principle is an appropriate one to underpin regulation. 1 The finding of the research is that autonomy can be justified as an organising principle on a number of grounds: it is consistent with the values of a liberal democracy; over recent decades, it is a principle that has been even more prominent within the discipline of medical ethics; and it is the principle which underpins the legal regulation of a related topic, namely the contemporaneous refusal of medical treatment. Next, the thesis reviews the common law to determine whether it effectively achieves the goal of promoting autonomy by allowing a competent adult to make an advance directive refusing treatment that will operate if he or she later loses decision-making capacity. 2 This research finds that conunon law doctrine, as espoused by the judiciary, prioritises individual choice by recognising valid advance directives that refuse treatment as binding. However, the research also concludes that the common law, as applied by the judiciary in some cases, may not be effective to promote individual autonomy, as there have been a number of circumstances where advance directives that refuse treatment have not been followed. The thesis then examines the statutory regimes in Australia that regulate advance directives, with a focus on the regulation of advance refusals of life-sustaining medical treatment.3 This review commences with an examination ofparliamentary debates to establish why legislation was thought to be necessary. It then provides a detailed review of all of the statutory regimes, the extent to which the legislation regulates the form of advance directives, and the circumstances in which they can be completed, will operate and can be ignored by medical professionals. The research finds that legislation was enacted mainly to clarify the common law and bring a level of certainty to the field. Legislative regimes were thought to provide medical professionals with the assurance that compliance with an advance directive that refuses life-sustaining medical treatment will not expose them to legal sanction. However, the research also finds that the legislation places so many restrictions on when an advance directive refusing treatment can be made, or will operate, that they have not been successful in promoting individual autonomy.

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In this paper we explore the ability of a recent model-based learning technique Receding Horizon Locally Weighted Regression (RH-LWR) useful for learning temporally dependent systems. In particular this paper investigates the application of RH-LWR to learn control of Multiple-input Multiple-output robot systems. RH-LWR is demonstrated through learning joint velocity and position control of a three Degree of Freedom (DoF) rigid body robot.

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Assessment for Learning (AfL) is an international assessment area of interest, yet, during 20 years of AfL research, the desired outcome of increased learner autonomy remains elusive. This article analyses AfL practices in classrooms as students negotiated identities as autonomous learners within a classroom community of practice. A sociocultural theoretical framework in formed the analysis of three case studies conducted in Queensland middle school classrooms. Key findings include the importance of the teacher–student relationship, viewing AfL as patterns of participation that develop expertise, and learner autonomy as a negotiated learner identity within each classroom context.

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Rats are superior to the most advanced robots when it comes to creating and exploiting spatial representations. A wild rat can have a foraging range of hundreds of meters, possibly kilometers, and yet the rodent can unerringly return to its home after each foraging mission, and return to profitable foraging locations at a later date (Davis, et al., 1948). The rat runs through undergrowth and pipes with few distal landmarks, along paths where the visual, textural, and olfactory appearance constantly change (Hardy and Taylor, 1980; Recht, 1988). Despite these challenges the rat builds, maintains, and exploits internal representations of large areas of the real world throughout its two to three year lifetime. While algorithms exist that allow robots to build maps, the questions of how to maintain those maps and how to handle change in appearance over time remain open. The robotic approach to map building has been dominated by algorithms that optimise the geometry of the map based on measurements of distances to features. In a robotic approach, measurements of distance to features are taken with range-measuring devices such as laser range finders or ultrasound sensors, and in some cases estimates of depth from visual information. The features are incorporated into the map based on previous readings of other features in view and estimates of self-motion. The algorithms explicitly model the uncertainty in measurements of range and the measurement of self-motion, and use probability theory to find optimal solutions for the geometric configuration of the map features (Dissanayake, et al., 2001; Thrun and Leonard, 2008). Some of the results from the application of these algorithms have been impressive, ranging from three-dimensional maps of large urban strucutures (Thrun and Montemerlo, 2006) to natural environments (Montemerlo, et al., 2003).

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This paper presents a method for automatic terrain classification, using a cheap monocular camera in conjunction with a robot’s stall sensor. A first step is to have the robot generate a training set of labelled images. Several techniques are then evaluated for preprocessing the images, reducing their dimensionality, and building a classifier. Finally, the classifier is implemented and used online by an indoor robot. Results are presented, demonstrating an increased level of autonomy.

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This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment

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Findings from a Queensland coronial inquest highlight the complex clinical, ethical and legal issues that arise in end-of-life care when clinicians and family members disagree about a diagnosis of clinical futility. The tension between the law and best medical practice is highlighted in this case, as doctors are compelled to seek family consent to not commence a futile intervention. Good communication between doctors and families, as well as community and professional education, is essential to resolve tensions that can arise when there is disagreement about treatment at the end of life.

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Appearance-based localization can provide loop closure detection at vast scales regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale not only with the size of the environment but also with the operation time of the platform. Additionally, repeated visits to locations will develop multiple competing representations, which will reduce recall performance over time. These properties impose severe restrictions on long-term autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. In this paper we present a graphical extension to CAT-SLAM, a particle filter-based algorithm for appearance-based localization and mapping, to provide constant computation and memory requirements over time and minimal degradation of recall performance during repeated visits to locations. We demonstrate loop closure detection in a large urban environment with capped computation time and memory requirements and performance exceeding previous appearance-based methods by a factor of 2. We discuss the limitations of the algorithm with respect to environment size, appearance change over time and applications in topological planning and navigation for long-term robot operation.

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This article proposes offence-specific guidelines for how prosecutorial discretion should be exercised in cases of voluntary euthanasia and assisted suicide. Similar guidelines have been produced in England and Wales but we consider them to be deficient in a number of respects, including that they lack a set of coherent guiding principles. In light of these concerns, we outline an approach to constructing alternative guidelines that begins with identifying three guiding principles that we argue are appropriate for this purpose: respect for autonomy, the need for high quality prosecutorial decision-making and the importance of public confidence in that decision-making.

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This paper describes an architecture for robotic telepresence and teleoperation based on the well known tools ROS and Skype. We discuss how Skype can be used as a framework for robotic communication and can be integrated into a ROS/Linux framework to allow a remote user to not only interact with people near the robot, but to view maps, sensory data, robot pose and to issue commands to the robot’s navigation stack. This allows the remote user to exploit the robot’s autonomy, providing a much more convenient navigation interface than simple remote joysticking.

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An increased interest in utilising groups of Unmanned Aerial Vehicles (UAVs) with heterogeneous capabilities and autonomy is presenting the challenge to effectively manage such during missions and operations. This has been the focus of research in recent years, moving from a traditional UAV management paradigm of n-to-1 (n operators for one UAV, with n being at least two operators) toward 1-to-n (one operator, multiple UAVs). This paper has expanded on the authors’ previous work on UAV functional capability framework, by incorporating the concept of Functional Level of Autonomy (F-LOA) with two configurations: The lower F-LOA configuration contains sufficient information for the operator to generate solutions and make decisions to address perturbation events. Alternatively, the higher F-LOA configuration presents information reflecting on the F-LOA of the UAV, allowing the operator to interpret solutions and decisions generated autonomously, and decide whether to veto from this decision.

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The construction of menopause as a long-term risk to health and the adoption of discourses of prevention has made necessary a decision by women about medical treatment; specifically regarding the use of hormone replacement therapy. In a study of general practitioners’ accounts of menopause and treatment in Australia, women's ‘choice’, ‘informed decision-making’ and ‘empowerment’ were key themes through which primary medical care for women at menopause was presented. These accounts create a position for women defined by the concept of individual choice and an ethic of autonomy. These data are a basis for theorising more generally in this paper. We critically examine the construct of ‘informed decision-making’ in relation to several approaches to ethics including bioethics and a range of feminist ethics. We identify the intensification of power relations produced by an ethic of autonomy and discuss the ways these considerations inform a feminist ethics of decision-making by women. We argue that an ‘ethic of autonomy’ and an ‘offer of choice’ in relation to health care for women at menopause, far from being emancipatory, serves to intensify power relations. The dichotomy of choice, to take or not to take hormone replacement therapy, is required to be a choice and is embedded in relations of power and bioethical discourse that construct meanings about what constitutes decision-making at menopause. The deployment of the principle of autonomy in medical practice limits decision-making by women precisely because it is detached from the construction of meaning and the self and makes invisible the relations of power of which it is a part.

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Stereo-based visual odometry algorithms are heavily dependent on an accurate calibration of the rigidly fixed stereo pair. Even small shifts in the rigid transform between the cameras can impact on feature matching and 3D scene triangulation, adversely affecting pose estimates and applications dependent on long-term autonomy. In many field-based scenarios where vibration, knocks and pressure change affect a robotic vehicle, maintaining an accurate stereo calibration cannot be guaranteed over long periods. This paper presents a novel method of recalibrating overlapping stereo camera rigs from online visual data while simultaneously providing an up-to-date and up-to-scale pose estimate. The proposed technique implements a novel form of partitioned bundle adjustment that explicitly includes the homogeneous transform between a stereo camera pair to generate an optimal calibration. Pose estimates are computed in parallel to the calibration, providing online recalibration which seamlessly integrates into a stereo visual odometry framework. We present results demonstrating accurate performance of the algorithm on both simulated scenarios and real data gathered from a wide-baseline stereo pair on a ground vehicle traversing urban roads.