Field and Service Robotics Results of the 5th International Conference

The 5th International Conference on Field and Service Robotics (FSR05) was held in Port Douglas, Australia, on 29th - 31st July 2005, and brought together the worlds' leading experts in field and service automation. The goal of the conference was to report and encourage the latest research and practical results towards the use of field and service robotics in the community with particular focus on proven technology. The conference provided a forum for researchers, professionals and robot manufacturers to exchange up-to-date technical knowledge and experience. Field robots are robots which operate in outdoor, complex, and dynamic environments. Service robots are those that work closely with humans, with particular applications involving indoor and structured environments. There are a wide range of topics presented in this issue on field and service robots including: Agricultural and Forestry Robotics, Mining and Exploration Robots, Robots for Construction, Security & Defence Robots, Cleaning Robots, Autonomous Underwater Vehicles and Autonomous Flying Robots. This meeting was the fifth in the series and brings FSR back to Australia where it was first held. FSR has been held every 2 years, starting with Canberra 1997, followed by Pittsburgh 1999, Helsinki 2001 and Lake Yamanaka 2003.

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.

A point interpolation method with locally smoothed strain field (PIM-LS2) for mechanics problems using triangular mesh

A point interpolation method with locally smoothed strain field (PIM-LS2) is developed for mechanics problems using a triangular background mesh. In the PIM-LS2, the strain within each sub-cell of a nodal domain is assumed to be the average strain over the adjacent sub-cells of the neighboring element sharing the same field node. We prove theoretically that the energy norm of the smoothed strain field in PIM-LS2 is equivalent to that of the compatible strain field, and then prove that the solution of the PIM- LS2 converges to the exact solution of the original strong form. Furthermore, the softening effects of PIM-LS2 to system and the effects of the number of sub-cells that participated in the smoothing operation on the convergence of PIM-LS2 are investigated. Intensive numerical studies verify the convergence, softening effects and bound properties of the PIM-LS2, and show that the very ‘‘tight’’ lower and upper bound solutions can be obtained using PIM-LS2.

Avoiding full extension field arithmetic in pairing computations

The most costly operations encountered in pairing computations are those that take place in the full extension field Fpk . At high levels of security, the complexity of operations in Fpk dominates the complexity of the operations that occur in the lower degree subfields. Consequently, full extension field operations have the greatest effect on the runtime of Miller’s algorithm. Many recent optimizations in the literature have focussed on improving the overall operation count by presenting new explicit formulas that reduce the number of subfield operations encountered throughout an iteration of Miller’s algorithm. Unfortunately, almost all of these improvements tend to suffer for larger embedding degrees where the expensive extension field operations far outweigh the operations in the smaller subfields. In this paper, we propose a new way of carrying out Miller’s algorithm that involves new explicit formulas which reduce the number of full extension field operations that occur in an iteration of the Miller loop, resulting in significant speed ups in most practical situations of between 5 and 30 percent.

Delaying mismatched field multiplications in pairing computations

Miller’s algorithm for computing pairings involves perform- ing multiplications between elements that belong to different finite fields. Namely, elements in the full extension field Fpk are multiplied by elements contained in proper subfields F pk/d , and by elements in the base field Fp . We show that significant speedups in pairing computations can be achieved by delaying these “mismatched” multiplications for an optimal number of iterations. Importantly, we show that our technique can be easily integrated into traditional pairing algorithms; implementers can exploit the computational savings herein by applying only minor changes to existing pairing code.

Metadata aggregation : a critical component of research infrastructure for the future

The development of research data management infrastructure and services and making research data more discoverable and accessible to the research community is a key priority at the national, state and individual university level. This paper will discuss and reflect upon a collaborative project between Griffith University and the Queensland University of Technology to commission a Metadata Hub or Metadata Aggregation service based upon open source software components. It will describe the role that metadata aggregation services play in modern research infrastructure and argue that this role is a critical one.

Ecology and bioprospecting

Bioprospecting is the exploration of biodiversity for new resources of social and commercial value. It is carried out by a wide range of established industries such as pharmaceuticals, manufacturing and agriculture as well as a wide range of comparatively new ones such as aquaculture, bioremediation, biomining, biomimetic engineering and nanotechnology. The benefits of bioprospecting have emerged from such a wide range of organisms and environments worldwide that it is not possible to predict what species or habitats will be critical to society, or industry, in the future. The benefits include an unexpected variety of products that include chemicals, genes, metabolic pathways, structures, materials and behaviours. These may provide physical blueprints or inspiration for new designs. Criticism aimed at bioprospecting has been addressed, in part, by international treaties and legal agreements aimed at stopping biopiracy and many activities are now funded by agencies that require capacity-building and economic benefits in host countries. Thus, much contemporary bioprospecting has multiple goals, including the conservation of biodiversity, the sustainable management of natural resources and economic development. Ecologists are involved in three vital ways: first, applying ecological principles to the discovery of new resources. In this context, natural history becomes a vast economic database. Second, carrying out field studies, most of them demographic, to help regulate the harvest of wild species. Third, emphasizing the profound importance of millions of mostly microscopic species to the global economy.

Resilience in critical infrastructures : the case of the Queensland electricity industry

The reliability of Critical Infrastructure is considered to be a fundamental expectation of modern societies. These large-scale socio-technical systems have always, due to their complex nature, been faced with threats challenging their ongoing functioning. However, increasing uncertainty in addition to the trend of infrastructure fragmentation has made reliable service provision not only a key organisational goal, but a major continuity challenge: especially given the highly interdependent network conditions that exist both regionally and globally. The notion of resilience as an adaptive capacity supporting infrastructure reliability under conditions of uncertainty and change has emerged as a critical capacity for systems of infrastructure and the organisations responsible for their reliable management. This study explores infrastructure reliability through the lens of resilience from an organisation and system perspective using two recognised resilience-enhancing management practices, High Reliability Theory (HRT) and Business Continuity Management (BCM) to better understand how this phenomenon manifests within a partially fragmented (corporatised) critical infrastructure industry – The Queensland Electricity Industry. The methodological approach involved a single case study design (industry) with embedded sub-units of analysis (organisations), utilising in-depth interviews and document analysis to illicit findings. Derived from detailed assessment of BCM and Reliability-Enhancing characteristics, findings suggest that the industry as a whole exhibits resilient functioning, however this was found to manifest at different levels across the industry and in different combinations. Whilst there were distinct differences in respect to resilient capabilities at the organisational level, differences were less marked at a systems (industry) level, with many common understandings carried over from the pre-corporatised operating environment. These Heritage Factors were central to understanding the systems level cohesion noted in the work. The findings of this study are intended to contribute to a body of knowledge encompassing resilience and high reliability in critical infrastructure industries. The research also has value from a practical perspective, as it suggests a range of opportunities to enhance resilient functioning under increasingly interdependent, networked conditions.

Development of pollutant build-up parameters for MIKE URBAN for Southeast Queensland, Australia

Accurate estimation of input parameters is essential to ensure the accuracy and reliability of hydrologic and water quality modelling. Calibration is an approach to obtain accurate input parameters for comparing observed and simulated results. However, the calibration approach is limited as it is only applicable to catchments where monitoring data is available. Therefore, methodology to estimate appropriate model input parameters is critical, particularly for catchments where monitoring data is not available. In the research study discussed in the paper, pollutant build-up parameters derived from catchment field investigations and model calibration using MIKE URBAN are compared for three catchments in Southeast Queensland, Australia. Additionally, the sensitivity of MIKE URBAN input parameters was analysed. It was found that Reduction Factor is the most sensitive parameter for peak flow and total runoff volume estimation whilst Build-up rate is the most sensitive parameter for TSS load estimation. Consequently, these input parameters should be determined accurately in hydrologic and water quality simulations using MIKE URBAN. Furthermore, an empirical equation for Southeast Queensland, Australia for the conversion of build-up parameters derived from catchment field investigations as MIKE URBAN input build-up parameters was derived. This will provide guidance for allowing for regional variations in the estimation of input parameters for catchment modelling using MIKE URBAN where monitoring data is not available.

Researching crime and violence: Untold stories from the field

Undertaking empirical research on crime and violence can be a tricky enterprise fraught with ethical, methodological, intellectual and legal implications. This chapter takes readers on a reflective journey through the qualitative methodologies I used to research sex work in Kings Cross, miscarriages of justice, female delinquency, sexual violence, and violence in rural and regional settings over a period of nearly 30 years. Reflecting on these experiences, the chapter explores and analyses the reality of doing qualitative field research, the role of the researcher, the politics of subjectivity, the exercise of power, and the ‘muddiness’ of the research process, which is often overlooked in sanitised accounts of the research process (Byrne-Armstrong, Higgs and Horsfall, 2001; Davies, 2000).