Reparations for Indigenous People: International and Comparative Perspectives

Published in concomitance with the adoption of the United Nations Declaration on the Rights of Indigenous Peoples, this volume brings together a group of renowned legal experts and activists from different parts of the world who, from international and comparative perspectives, investigate the right of indigenous peoples to reparation for breaches of their individual and collective rights. The first part of the book is devoted to general aspects of this important matter, providing a comprehensive assessment of the relevant international legal framework and including overviews of the topic of reparations for human rights violations, the status of indigenous peoples in international law, and the vision of reparations as conceived by the communities concerned. The second part embraces a comprehensive investigation of the relevant practice at the international, regional, and national level, examining the best practices of reparations according to the ideologies and expectations of indigenous peoples and offering a comparative perspective on the ways in which the right of these peoples to redress for the injuries suffered is realized worldwide. The global picture painted by these contributions provides a view of the status of relevant international law that is synthesized in the two final chapters of the book, which include a concrete example of how a judicial claim for reparation is to be structured and prescribes the best practices and strategies to be adopted in order to maximize the opportunities for indigenous peoples to obtain effective redress. As a whole, this volume offers a comprehensive vision of its subject matter in international and comparative law, with a practical approach aimed at supporting legal academics, administrators, and practitioners in improving the avenues and modalities of reparations for indigenous peoples

Meeting and greeting : activities in public outdoor spaces outside high-density urban residential communities

This paper examines the opportunities for social activities in public outdoor spaces associated with high-density residential living. This study surveyed activities in outdoor spaces outside three high-density residential communities in Brisbane. Results indicated that activity patterns in public outdoor space outside residential communities are different to general urban public outdoor space. This broadly but not fully supports current theories concerning activities in public space. That is some environmental factors have impacts on the level of social interaction. The relationship between outdoor space and a residential building may have a significant impact on the level of social activities. As a consequence, a new classification of activities in public space is suggested. In improving the level of social contact in public outdoor space outside a residential community, the challenge is how to encourage people to leave their comfortable homes and spend a short time in these public spaces. For residential buildings and public space to be treated as an integrated whole, the outdoor open spaces close to and surrounding these buildings must have a more welcoming design.

MATLAB toolboxes : robotics and vision for students and teachers

In this column, Dr. Peter Corke of CSIRO, Australia, gives us a description of MATLAB Toolboxes he has developed. He has been passionately developing tools to enable students and teachers to better understand the theoretical concepts behind classical robotics and computer vision through easy and intuitive simulation and visualization. The results of this labor of love have been packaged as MATLAB Toolboxes: the Robotics Toolbox and the Vision Toolbox. –Daniela Rus, RAS Education Cochair

High dynamic range stereo vision for outdoor mobile robotics

We present a technique for high-dynamic range stereo for outdoor mobile robot applications. Stereo pairs are captured at a number of different exposures (exposure bracketing), and combined by projecting the 3D points into a common coordinate frame, and building a 3D occupancy map. We present experimental results for static scenes with constant and dynamic lighting as well as outdoor operation with variable and high contrast lighting conditions.

A Vision for saving the reef — the Starbug AUV

Starbug is an inexpensive, miniature autonomous underwater vehicle ideal for data collection and ecosystem surveys. Starbug is small enough to be launched by one person without the need for specialised equipment, such as cranes, and it operates with minimal to no human intervention. Starbug was one of the first autonomous underwater vehicles (AUVs) in the world where vision is the primary means of navigation and control. More details of Starbug can be found here: http://www.csiro.au/science/starbug.html

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.

The Machine Vision Toolbox : A MATLAB Toolbox for vision and vision-based control

The article described an open-source toolbox for machine vision called Machine Vision Toolbox (MVT). MVT includes more than 60 functions including image file reading and writing, acquisition, display, filtering, blob, point and line feature extraction, mathematical morphology, homographies, visual Jacobians, camera calibration, and color space conversion. MVT can be used for research into machine vision but is also versatile enough to be usable for real-time work and even control. MVT, combined with MATLAB and a model workstation computer, is a useful and convenient environment for the investigation of machine vision algorithms. The article illustrated the use of a subset of toolbox functions for some typical problems and described MVT operations including the simulation of a complete image-based visual servo system.

Low-Cost vision-based AUV guidance system for reef navigation

Ensuring the long term viability of reef environments requires essential monitoring of many aspects of these ecosystems. However, the sheer size of these unstructured environments (for example Australia’s Great Barrier Reef pose a number of challenges for current monitoring platforms which are typically remote operated and required significant resources and infrastructure. Therefore, a primary objective of the CSIRO robotic reef monitoring project is to develop and deploy a large number of AUV teams to perform broadscale reef surveying. In order to achieve this, the platforms must be cheap, even possibly disposable. This paper presents the results of a preliminary investigation into the performance of a low-cost sensor suite and associated processing techniques for vision and inertial-based navigation within a highly unstructured reef environment.

Visual servoing of a car-like vehicle - an application of omnidirectional vision

In this paper, we develop the switching controller presented by Lee et al. for the pose control of a car-like vehicle, to allow the use of an omnidirectional vision sensor. To this end we incorporate an extension to a hypothesis on the navigation behaviour of the desert ant, cataglyphis bicolor, which leads to a correspondence free landmark based vision technique. The method we present allows positioning to a learnt location based on feature bearing angle and range discrepancies between the robot's current view of the environment, and that at a learnt location. We present simulations and experimental results, the latter obtained using our outdoor mobile platform.

What health services within rural communities tell us about Aboriginal people and Aboriginal health

There is a growing body of literature within social and cultural geography that explores notions of place, space, culture, race and identity. When health services in rural communities are explored using these notions, it can lead to multiple ways of understanding the cultural meanings inscribed within health services and how they can be embedded with an array of politics. For example, health services can often reflect the symbolic place that each individual holds within that rural community. Through the use of a rural health service case study, this paper will demonstrate how the physical sites and appearances of health services can act as social texts that convey messages of belonging and welcome, or exclusion and domination. They can also produce and reproduce power and control relations. In this way, they can influence the ways that Aboriginal people engage in health service environments – either as places where Aboriginal people feel welcome, comfortable, secure and culturally safe and happy to use the health service, or as places where they utilise the service provided with a great deal of effort, angst and energy. It is important to understand how these complex notions play out in rural communities if the health and wellbeing of Aboriginal people is going to be addressed.

Narratives for novices : is there a place for edgy texts in edgy NAPLAN communities?

The genre of narratives has become the genre of choice in many classrooms since the introduction of NAPLAN into Australian schools. Yet, Knapp and Watkins (2005) argue that narratives are the least understood of all the genres. Despite wide-spread acceptance that narratives serve the social purpose of entertaining, they can also be more edgy, offering a powerful social or information role. This paper considers the effects of exposing novices to less standard realms of social discourse and disciplinary knowledge vis-a-vis a more clinical treatment focused on ‘standard’ narratives. I argue that we should not shy away from the challenges of edgy narratives just because our students are novice readers. The same holds true for our work in communities on the edge, that is where poverty, multiculturalism or multilingualism and systemic failure are the norm. I am part of an Australian Research Council (ARC) Linkage Grant (LP 0990289) working in such a community. Like many such situations, teachers in these communities are caught in the fray of establishing a dialogue between the culture of federally mandated performance orientated reforms and the cultures and discourses of the lives and future needs of their students (see Exley & Singh, in press).

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.