Visual motion estimation for an autonomous underwater reef monitoring robot

Performing reliable localisation and navigation within highly unstructured underwater coral reef environments is a difficult task at the best of times. Typical research and commercial underwater vehicles use expensive acoustic positioning and sonar systems which require significant external infrastructure to operate effectively. This paper is focused on the development of a robust vision-based motion estimation technique using low-cost sensors for performing real-time autonomous and untethered environmental monitoring tasks in the Great Barrier Reef without the use of acoustic positioning. The technique is experimentally shown to provide accurate odometry and terrain profile information suitable for input into the vehicle controller to perform a range of environmental monitoring tasks.

Vision-based navigational competencies for a car-like vehicle

If mobile robots are to perform useful tasks in the real-world they will require a catalog of fundamental navigation competencies and a means to select between them. In this paper we describe our work on strongly vision-based competencies: road-following, person or vehicle following, pose and position stabilization. Results from experiments on an outdoor autonomous tractor, a car-like vehicle, are presented.

In the Rough : In-Field evaluation of an autonomous vehicle for golf course maintenance

Maintenance is a time consuming and expensive task for any golf course or driving range manager. For a golf course the primary tasks are grass mowing and maintenance (fertilizer and herbicide spreading), while for a driving range mowing, maintenance and ball collection are required. All these tasks require an operator to drive a vehicle along paths which are generally predefined. This paper presents some preliminary in-field tsting results for an automated tractor vehicle performing golf ball collection on an actual driving range, and mowing on difficult unstructured terrain.

Performance tests for visual servo control systems, with application to partitioned approaches to visual servo control

Visual servoing has been a viable method of robot manipulator control for more than a decade. Initial developments involved positionbased visual servoing (PBVS), in which the control signal exists in Cartesian space. The younger method, image-based visual servoing (IBVS), has seen considerable development in recent years. PBVS and IBVS offer tradeoffs in performance, and neither can solve all tasks that may confront a robot. In response to these issues, several methods have been devised that partition the control scheme, allowing some motions to be performed in the manner of a PBVS system, while the remaining motions are performed using an IBVS approach. To date, there has been little research that explores the relative strengths and weaknesses of these methods. In this paper we present such an evaluation. We have chosen three recent visual servo approaches for evaluation in addition to the traditional PBVS and IBVS approaches. We posit a set of performance metrics that measure quantitatively the performance of a visual servo controller for a specific task. We then evaluate each of the candidate visual servo methods for four canonical tasks with simulations and with experiments in a robotic work cell.

Overview of the INEX 2009 XML mining track : clustering and classification of XML documents

This report explains the objectives, datasets and evaluation criteria of both the clustering and classification tasks set in the INEX 2009 XML Mining track. The report also describes the approaches and results obtained by the different participants.

Design Optimisation of UAVs Systems achieved on a Framework Environment via Evolution and Game Theory

Over recent years, Unmanned Air Vehicles or UAVs have become a powerful tool for reconnaissance and surveillance tasks. These vehicles are now available in a broad size and capability range and are intended to fly in regions where the presence of onboard human pilots is either too risky or unnecessary. This paper describes the formulation and application of a design framework that supports the complex task of multidisciplinary design optimisation of UAVs systems via evolutionary computation. The framework includes a Graphical User Interface (GUI), a robust Evolutionary Algorithm optimiser named HAPEA, several design modules, mesh generators and post-processing capabilities in an integrated platform. These population –based algorithms such as EAs are good for cases problems where the search space can be multi-modal, non-convex or discontinuous, with multiple local minima and with noise, and also problems where we look for multiple solutions via Game Theory, namely a Nash equilibrium point or a Pareto set of non-dominated solutions. The application of the methodology is illustrated on conceptual and detailed multi-criteria and multidisciplinary shape design problems. Results indicate the practicality and robustness of the framework to find optimal shapes and trade—offs between the disciplinary analyses and to produce a set of non dominated solutions of an optimal Pareto front to the designer.

Spaces of hybridity : creating a sense of belonging through spatial awareness

When the colonisers first came to Australia there was an urgent desire to map, name and settle. This desire, in part, stemmed from a fear of the unknown. Once these tasks were completed it was thought that a sense of identity and belonging would automatically come. In Anglo-Australian geography the map of Australia was always perceived in relationship to the larger map of Europe and Britain. The quicker Australia could be mapped the quicker its connection with the ‘civilised’ world could be established. Official maps could be taken up in official history books and a detailed monumental history could begin. Australians would feel secure in where they were placed in the world. However, this was not the case and anxieties about identity and belonging remained. One of the biggest hurdles was the fear of the open spaces and not knowing how to move across the land. Attempts to transpose colonisers’ use of space onto the Australian landscape did not work and led to confusion. Using authors who are often perceived as writers of national fictions (Henry Lawson, Barbara Baynton, Patrick White, David Malouf and Peter Carey) I will reveal how writing about space becomes a way to create a sense of belonging. It is through spatial knowledge and its application that we begin to gain a sense of closeness and identity. I will also look at how one of the greatest fears for the colonisers was the Aboriginal spatial command of the country. Aborigines already had a strongly developed awareness of spatial belonging and their stories reveal this authority (seen in the work of Lorna Little, Mick McLean) Colonisers attempted to discredit this knowledge but the stories and the land continue to recognise its legitimacy. From its beginning Australian spaces have been spaces of hybridity and the more the colonisers attempted to force predetermined structures onto these spaces the more hybrid they became.

Technical report : acoustic analysis of the natural environment

This technical report is concerned with one aspect of environmental monitoring—the detection and analysis of acoustic events in sound recordings of the environment. Sound recordings offer ecologists the potential advantages of cheaper and increased sampling. An acoustic event detection algorithm is introduced that outputs a compact rectangular marquee description of each event. It can disentangle superimposed events, which are a common occurrence during morning and evening choruses. Next, three uses to which acoustic event detection can be put are illustrated. These tasks have been selected because they illustrate quite different modes of analysis: (1) the detection of diffuse events caused by wind and rain, which are a frequent contaminant of recordings of the terrestrial environment; (2) the detection of bird calls using the spatial distribution of their component events; and (3) the preparation of acoustic maps for whole ecosystem analysis. This last task utilises the temporal distribution of events over a daily, monthly or yearly cycle.

Graduate research capabilities : a new agenda for research supervisors

There has been a conversation about university graduate employability within the Higher Education literature for some time (Cryer, 1997; Barrie, 2004, 2006, 2007; Murray, 2000; McAlpine, 2005). Within this, and often under the banner of questioning the relevance of the PhD (Murray, 2000), there have been discussions about the employability of research postgraduates. Both the broad discussion of graduate employment and the specific discussion of research degree graduate employment have produced an agenda of graduate research capabilities. Traditionally, assisting research higher degree (RHD) students with their career development has not been an articulated part of the research supervision process. However, the graduate research capabilities agenda has added a new element to the practices of research supervision, in that it brings with it a mandate for research graduates to be aware of the range of capabilities they have acquired through their research degree candidature and how these apply in the workforce. Additionally, there is an emphasis on preparing students for varied career paths rather than a traditional academic route (e.g., in industry or government). Supervisors have a vital role to play in assisting students with these important career development tasks. In this practice application brief we report on a strategy recently used at Queensland University of Technology (QUT) to assist supervisors understand their role in a student’s career development.

Large margin vector quantization

In this paper we describe the Large Margin Vector Quantization algorithm (LMVQ), which uses gradient ascent to maximise the margin of a radial basis function classifier. We present a derivation of the algorithm, which proceeds from an estimate of the class-conditional probability densities. We show that the key behaviour of Kohonen's well-known LVQ2 and LVQ3 algorithms emerge as natural consequences of our formulation. We compare the performance of LMVQ with that of Kohonen's LVQ algorithms on an artificial classification problem and several well known benchmark classification tasks. We find that the classifiers produced by LMVQ attain a level of accuracy that compares well with those obtained via LVQ1, LVQ2 and LVQ3, with reduced storage complexity. We indicate future directions of enquiry based on the large margin approach to Learning Vector Quantization.

Nursing resource implications of the unoccupied bed

Objective: To explore the specific factors that impact on nursing resources in relation to the ‘unoccupied bed’. Design: Descriptive observational Setting: Multiple wards in single site, tertiary referral hospital Main outcome measure: Identification and classification of tasks related to the unoccupied bed. Results: Our study identified three main areas of nursing work, which centre on the ‘unoccupied bed’: 1) bed preparation for admission; 2) temporary transfer; 3) bed preparation post patient discharge. Conclusion: The unoccupied bed is not resource neutral and may involve considerable nursing time. The time associated with each of the reasons for the bed being unoccupied remains to be quantified.

Analysis of primary user duty cycle impact on spectrum sensing performance

Spectrum sensing is considered to be one of the most important tasks in cognitive radio. Many sensing detectors have been proposed in the literature, with the common assumption that the primary user is either fully present or completely absent within the window of observation. In reality, there are scenarios where the primary user signal only occupies a fraction of the observed window. This paper aims to analyse the effect of the primary user duty cycle on spectrum sensing performance through the analysis of a few common detectors. Simulations show that the probability of detection degrades severely with reduced duty cycle regardless of the detection method. Furthermore we show that reducing the duty cycle has a greater degradation on performance than lowering the signal strength.

Body size and walking cadence affect lower extremity joint power in children's gait

Obese children move less and with greater difficulty than normal-weight counterparts but expend comparable energy. Increased metabolic costs have been attributed to poor biomechanics but few studies have investigated the influence of obesity on mechanical demands of gait. This study sought to assess three-dimensional lower extremity joint powers in two walking cadences in 28 obese and normal-weight children. 3D-motion analysis was conducted for five trials of barefoot walking at self-selected and 30% greater than self-selected cadences. Mechanical power was calculated at the hip, knee, and ankle in sagittal, frontal and transverse planes. Significant group differences were seen for all power phases in the sagittal plane, hip and knee power at weight acceptance and hip power at propulsion in the frontal plane, and knee power during mid-stance in the transverse plane. After adjusting for body weight, group differences existed in hip and knee power phases at weight acceptance in sagittal and frontal planes, respectively. Differences in cadence existed for all hip joint powers in the sagittal plane and frontal plane hip power at propulsion. Frontal plane knee power at weight acceptance and sagittal plane knee power at propulsion were significantly different between cadences. Larger joint powers in obese children contribute to difficulty performing locomotor tasks, potentially decreasing motivation to exercise.

QoS-oriented sesource allocation and scheduling of multiple composite web services in a hybrid cloud using a random-key genetic algorithm

In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.

A dog of a QCAT : collateral effects of mandated English assessment in the Torres Strait

This paper critiques a 2008 Queensland Studies Authority (QSA) assessment initiative known as Queensland Comparable Assessment Tasks, or QCATs. The rhetoric is that these centrally devised assessment tasks will provide information about how well students can apply what they know, understand and can do in different contexts (QSA, 2009). The QCATs are described as ‘authentic, performance-based assessment’ that involves a ‘meaningful problem’, ‘emphasises critical thinking and reasoning’ and ‘provides students with every opportunity to do their best work’ (QSA, 2009). From my viewpoint as a teacher, I detail my professional concerns with implementing the 2008 middle primary English QCAT in one case study Torres Strait Island community. Specifically I ask ‘QCATs: Comparable with what?’ and ‘QCATs: Whose authentic assessment?’. I predict the possible collateral effects of implementing this English assessment in this remote Indigenous community, concluding, rather than being an example of quality assessment, colloquially speaking, it is nothing more than a ‘dog’.