Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes

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.

ACE research briefing paper 004 : emerging and young high potential start-ups

In this report we take a look at what separates high potential emerging and young start-ups from others. We compare the characteristics, intentions and behaviours of start-ups that we judge to be 'high potential' with other start-ups. We utilise the first two years of data from the CAUSEE study. We also compare Australian start-ups with a similar study conduced in the US.

OpenFABMAP : an open source toolbox for appearance-based loop closure detection

Appearance-based loop closure techniques, which leverage the high information content of visual images and can be used independently of pose, are now widely used in robotic applications. The current state-of-the-art in the field is Fast Appearance-Based Mapping (FAB-MAP) having been demonstrated in several seminal robotic mapping experiments. In this paper, we describe OpenFABMAP, a fully open source implementation of the original FAB-MAP algorithm. Beyond the benefits of full user access to the source code, OpenFABMAP provides a number of configurable options including rapid codebook training and interest point feature tuning. We demonstrate the performance of OpenFABMAP on a number of published datasets and demonstrate the advantages of quick algorithm customisation. We present results from OpenFABMAP’s application in a highly varied range of robotics research scenarios.

Action’s place in the venture creation process

This study examined the effect that venture creation action has on the outcomes of nascent entrepreneurship. A conceptual model was developed which proposes action as a fundamental mechanism in venture creation. Thus, action should rightly be considered as a means which transmits the effects of venture resource endowments on to venture creation outcomes. This conceptual model was empirically supported in a random sample of nascent ventures. Ventures with higher levels of human or social capital were found to be more active in venture creation. In turn, more active venture attempts were more likely to achieve improved venture creation outcomes. Further, human and social capital, on their own, exhibit little direct influence on the venture outcomes achieved. These findings confirm action’s central place in the venture creation process.

Performing design analysis: game design creativity and the theatre of the impressed

We report and reflect upon the early stages of a research project that endeavours to establish a culture of critical design thinking in a tertiary game design course. We first discuss the current state of the Australian game industry and consider some perceived issues in game design courses and graduate outcomes. The second sec-tion presents our response to these issues: a project in progress which uses techniques originally exploited by Augusto Boal in his work, Theatre of the Oppressed. We appropriate Boal’s method to promote critical design thinking in a games design class. Finally, we reflect on the project and the ontology of design thinking from the perspective of Bruce Archer’s call to reframe design as a ‘third academic art’.

Beyond here-and-now : extending shared physical experiences to shared conceptual experiences

For robots to use language effectively, they need to refer to combinations of existing concepts, as well as concepts that have been directly experienced. In this paper, we introduce the term generative grounding to refer to the establishment of shared meaning for concepts referred to using relational terms. We investigated a spatial domain, which is both experienced and constructed using mobile robots with cognitive maps. The robots, called Lingodroids, established lexicons for locations, distances, and directions through structured conversations called where-are-we, how-far, what-direction, and where-is-there conversations. Distributed concept construction methods were used to create flexible concepts, based on a data structure called a distributed lexicon table. The lexicon was extended from words for locations, termed toponyms, to words for the relational terms of distances and directions. New toponyms were then learned using these relational operators. Effective grounding was tested by using the new toponyms as targets for go-to games, in which the robots independently navigated to named locations. The studies demonstrate how meanings can be extended from grounding in shared physical experiences to grounding in constructed cognitive experiences, giving the robots a language that refers to their direct experiences, and to constructed worlds that are beyond the here-and-now.

Towards persistent localization and mapping with a continuous appearance-based topology

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.

SeqSLAM : visual route-based navigation for sunny summer days and stormy winter nights

Learning and then recognizing a route, whether travelled during the day or at night, in clear or inclement weather, and in summer or winter is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual navigation under changing conditions dubbed SeqSLAM. Instead of calculating the single location most likely given a current image, our approach calculates the best candidate matching location within every local navigation sequence. Localization is then achieved by recognizing coherent sequences of these “local best matches”. This approach removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. The approach is applicable over environment changes that render traditional feature-based techniques ineffective. Using two car-mounted camera datasets we demonstrate the effectiveness of the algorithm and compare it to one of the most successful feature-based SLAM algorithms, FAB-MAP. The perceptual change in the datasets is extreme; repeated traverses through environments during the day and then in the middle of the night, at times separated by months or years and in opposite seasons, and in clear weather and extremely heavy rain. While the feature-based method fails, the sequence-based algorithm is able to match trajectory segments at 100% precision with recall rates of up to 60%.

Capping computation time and storage requirements for appearance-based localization with CAT-SLAM

Appearance-based localization is increasingly used for loop closure detection in metric SLAM systems. Since it relies only upon the appearance-based similarity between images from two locations, it can perform loop closure regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale linearly not only with the size of the environment but also with the operation time of the platform. These properties impose severe restrictions on longterm autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. We present a set of improvements to the appearance-based SLAM algorithm CAT-SLAM to constrain computation scaling and memory usage with minimal degradation in performance over time. The appearance-based comparison stage is accelerated by exploiting properties of the particle observation update, and nodes in the continuous trajectory map are removed according to minimal information loss criteria. We demonstrate constant time and space loop closure detection in a large urban environment with recall performance exceeding FAB-MAP by a factor of 3 at 100% precision, and investigate the minimum computational and memory requirements for maintaining mapping performance.

Introduction

This introduction examines sixteen authors who have contributed to New Voices, New Visions: Challenging Australian Identities and Legacies. The editors explain that the authors draw on ideas, concepts, and theories about nation, identity, space, place,and power in order to rethink stories or reread large-scale and everyday media, private, or public events in new ways. In many cases, the authors are promoting debate on topics where a single viewpoint currently predominates. These authors are introducing to readers new visions and new voices about Australian society and the Australian identity. The editors also draw on the many books about Captain/Governor William Bligh to exemplify how history is constantly being reinterpreted, with new information aiding the reader’s understanding.

White Lines: The Intercultural Politics of Everyday Movement in Local Spaces

This article draws on research into racist vilification experienced by young Arab and Muslim Australians especially since 11 September 2001, to explore the links between public space, movement and national belonging, and the spatial regulation of cultural difference that functions in Australia. The authors analyse the way that the capacity to experience forms of national belonging and cultural citizenship is shaped by inclusion within or exclusion from local as well as nationally significant public spaces. While access to public space and freedom to move are conventionally seen as fundamental to a democratic state, these are often seen in abstract terms. This article emphasises how movement in public space is a very concrete dimension of our experience of freedom, in showing how incivilities directed against Arab and Muslim Australians have operated pedagogically as a spatialised regulation of national belonging. The article concludes by examining how processes associated with the Cronulla riots of December 2005 have retarded the capacities of Muslim and Arab Australians to negotiate within and across spaces, diminishing their opportunities to invest in local and national spaces, shrinking their resources and opportunities for place-making in public space.

The Working After Cancer Study (WACS): a population-based study of middle-aged workers diagnosed with colorectal cancer and their return to work experiences

Background The number of middle-aged working individuals being diagnosed with cancer is increasing and so too will disruptions to their employment. The aim of the Working After Cancer Study is to examine the changes to work participation in the 12 months following a diagnosis of primary colorectal cancer. The study will identify barriers to work resumption, describe limitations on workforce participation, and evaluate the influence of these factors on health-related quality of life. Methods/Design An observational population-based study has been designed involving 260 adults newly-diagnosed with colorectal cancer between January 2010 and September 2011 and who were in paid employment at the time they were diagnosed. These cancer cases will be compared to a nationally representative comparison group of 520 adults with no history of cancer from the general population. Eligible cases will have a histologically confirmed diagnosis of colorectal cancer and will be identified through the Queensland Cancer Registry. Data on the comparison group will be drawn from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. Data collection for the cancer group will occur at 6 and 12 months after diagnosis, with work questions also asked about the time of diagnosis, while retrospective data on the comparison group will be come from HILDA Waves 2009 and 2010. Using validated instruments administered via telephone and postal surveys, data will be collected on socio-demographic factors, work status and circumstances, and health-related quality of life (HRQoL) for both groups while the cases will have additional data collected on cancer treatment and symptoms, work productivity and cancer-related HRQoL. Primary outcomes include change in work participation at 12 months, time to work re-entry, work limitations and change in HRQoL status. Discussion This study will address the reasons for work cessation after cancer, the mechanisms people use to remain working and existing workplace support structures and the implications for individuals, families and workplaces. It may also provide key information for governments on productivity losses.