An investigation on the accuracy of regional ocean models through field trials

Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.

The clay-size fraction of CI chondrites Alais and Orgueil : an AEM study

CI chondrites are used pervasively in the meteorite literature as a cosmochemical reference point for bulk compositions[1], isotope analyses[2] and, within certain models of meteorite evolution, as an important component of an alteration sequence within the carbonaceous chondrite subset[3]. More recently, the chemical variablity of CI chondrite matrices (which comprise >80% of the meteorite), has been cited in discussions about the "chondritic" nature of spectroscopic data from P/comet Halley missions[4] and of chemical data from related materials such as interplanetary dust particles[5]. Most CI chondrites have been studied as bulk samples(e.g. major and trace element abundances)and considerable effort has also been focussed on accessory phases such as magnetites, olivine, sulphates and carbonates [6-8]. A number of early studies showed that the primary constituents of CI matrices are layer silicates and the most definitive structural study on powdered samples identified two minerals: montmorillonite and serpentine[9]. In many cases, as with the study by Bass[9],the relative scarcity of most CI chondrites restricts such bulk analyses to the Orgueil meteorite. The electron microprobe/SEM has been used on petrographic sections to more precisely define the "bulk" composition of at least four CI matrices[3], and as recently summarised by McSween[3], these data define a compositional trend quite different to that obtained for CM chondrite matrices. These "defocussed-beam" microprobe analyses average major element compositions over matrix regions ~lOOµm in diameter and provide only an approximation to silicate mineral composition(s) because their grain sizes are much less than the diameter of the beam. In order to (a) more precisely define the major element compositions of individual mineral grains within CI matrices, and (b)complement previous TEM studies [11,12], we have undertaken an analytical electron microscopy (AEM) study of Alais and Orgueil matrices.

Management of heterogeneous UAVs through a capability framework of UAV’s functional autonomy

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.

Adaptive dynamic path re-planning RRT algorithms with game theory for UAVs

The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.

Delphi study for improving sustainable construction project management in universities

As sustainability becomes an important principle guiding various human activities around the globe, the higher education sector is being asked to take an active part in educating and promoting sustainability due to its moral responsibility, social obligation and its own needs to adapt to new circumstances. There is a global trend of higher education institutions embarking on responses to the sustainability challenge. On-campus building performance is one of the most important indicators for “sustainable universities”, because buildings carry substantially environmental burden such as considerable consumption of raw materials and energy as well as huge amount of waste generation and greenhouse gas emission. Plus, much research proves that building performance can impact on students and staff’s awareness about and behaviours related to sustainability. The past studies rarely discussed about sustainable construction projects in universities’ unique context. Universities are labeled with distinct characteristics such as complex governance, multiple cultures and juggling missions and so on. It is necessary and meaningful to examine the project management system in terms of universities’ organizational environment. Thus, this research project applies Delphi study to identify primary barriers to green technology application in on-campus buildings, critical factors for sustainable project success, key actions in project phases and strategies for project improvement. Through three rounds of questionnaires among panel experts, the authors obtain a profound understanding of project delivery system in universities. The research results are expected to provide sustainability practitioners with holistic understanding and generic information about sustainable construction project performance on campus as an assistance tool.

Morphology of osteocyte cells in normal and hyper-gravity

Osteocyte cells are the most abundant cells in human bone tissue. Due to their unique morphology and location, osteocyte cells are thought to act as regulators in the bone remodelling process, and are believed to play an important role in astronauts’ bone mass loss after long-term space missions. There is increasing evidence showing that an osteocyte’s functions are highly affected by its morphology. However, changes in an osteocyte’s morphology under an altered gravity environment are still not well documented. Several in vitro studies have been recently conducted to investigate the morphological response of osteocyte cells to the microgravity environment, where osteocyte cells were cultured on a two-dimensional flat surface for at least 24 hours before microgravity experiments. Morphology changes of osteocyte cells in microgravity were then studied by comparing the cell area to 1g control cells. However, osteocyte cells found in vivo are with a more 3D morphology, and both cell body and dendritic processes are found sensitive to mechanical loadings. A round shape osteocyte’s cells support a less stiff cytoskeleton and are more sensitive to mechanical stimulations compared with flat cellular morphology. Thus, the relative flat and spread shape of isolated osteocytes in 2D culture may greatly hamper their sensitivity to a mechanical stimulus, and the lack of knowledge on the osteocyte’s morphological characteristics in culture may lead to subjective and noncomprehensive conclusions of how altered gravity impacts on an osteocyte’s morphology. Through this work empirical models were developed to quantitatively predicate the changes of morphology in osteocyte cell lines (MLO-Y4) in culture, and the response of osteocyte cells, which are relatively round in shape, to hyper-gravity stimulation has also been investigated. The morphology changes of MLO-Y4 cells in culture were quantified by measuring cell area and three dimensionless shape features including aspect ratio, circularity and solidity by using widely accepted image analysis software (ImageJTM). MLO-Y4 cells were cultured at low density (5×103 per well) and the changes in morphology were recorded over 10 hours. Based on the data obtained from the imaging analysis, empirical models were developed using the non-linear regression method. The developed empirical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analysing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary. The morphological response of MLO-Y4 cells with a relatively round morphology to hyper-gravity environment has been investigated using a centrifuge. After 2 hours culture, MLO-Y4 cells were exposed to 20g for 30mins. Changes in the morphology of MLO-Y4 cells are quantitatively analysed by measuring the average value of cell area and dimensionless shape factors such as aspect ratio, solidity and circularity. In this study, no significant morphology changes were detected in MLO-Y4 cells under a hyper-gravity environment (20g for 30 mins) compared with 1g control cells.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Experimental evaluation of an autonomous surface vehicle for water quality and greenhouse gas emission monitoring

This paper describes the experimental evaluation of a novel Autonomous Surface Vehicle capable of navigating complex inland water reservoirs and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran is capable of collecting water column profiles whilst in motion. It is also directly integrated with a reservoir scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper describes the onboard vehicle navigation and control algorithms as well as obstacle avoidance strategies. Experimental results are shown demonstrating its ability to maintain track and avoid obstacles on a variety of large-scale missions and under differing weather conditions, as well as its ability to continuously collect various water quality parameters complimenting traditional manual monitoring campaigns.

Indigenous Australian women and work : an historical context

The aim of this on-going research is to interrogate the era of colonialism in Australia (1896-1966) and the denial of paid employment of Aboriginal women. The 1897 Aborigines Protection and the Restriction of the Sale of Opium Act witnessed thousands of Aboriginal people placed on Government run reserves and missions. This resulted in all aspects of their lives being controlled through state mechanisms. Under various Acts of Parliament, Aboriginal women were sent to privately owned properties to be utilised as ‘domestic servants’ through a system of forced indentured labour, which continued until the 1970’s. This paper discusses the hidden histories of these women through the use of primary sources documents including records from the Australian Department of Native Affairs and Department of Home and Health. This social history research reveals that the practice of removing Aboriginal women from their families at the age of 12 or 13 and to white families was more common practice than not. These women were often: not paid, worked up to 15 hour days, not allowed leave and subjected to many forms of abuse. Wages that were meant to be paid were re-directed to other others, including the Government. Whilst the retrieval of these ‘stolen wages’ is now an on-going issue resulting in the Queensland Government in 2002 offering AUS $2,000 to $4,000 in compensation for a lifetime of work, Aboriginal women were also asked to waive their legal right to further compensation. There are few documented histories of these Aboriginal women as told through the archives. This hidden Aboriginal Australian women’s history needs to be revealed to better understand the experiences and depth of misappropriation of Aboriginal women as domestic workers. In doing so, it also reveals a more accurate reflection of women’s work in Australia.

Enhanced stochastic mobility prediction with multi-output Gaussian processes

Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain.

Regional trade-offs between mine water and energy use : a water treatment case study

The mining industry faces concurrent pressures of reducing water use, energy consumption and greenhouse gas (GHG) emissions in coming years. However, the interactions between water and energy use, as well as GHG e missions have largely been neglected in modelling studies to date. In addition, investigations tend to focus on the unit operation scale, with little consideration of whole-of-site or regional scale effects. This paper presents an application of a hierarchical systems model (HSM) developed to represent water, energy and GHG emissions fluxes at scales ranging from the unit operation, to the site level, to the regional level. The model allows for the linkages between water use, energy use and GHG emissions to be examined in a fl exible and intuitive way, so that mine sites can predict energy and emissions impacts of water use reduction schemes and vice versa. This paper examines whether this approach can also be applied to the regional scale with multiple mine sites. The model is used to conduct a case study of several coal mines in the Bowen Basin, Australia, to compare the utility of centralised and decentralised mine water treatment schemes. The case study takes into account geographical factors (such as water pumping distances and elevations), economic factors (such as capital and operating cost curves for desalination treatment plants) and regional factors (such as regionally varying climates and associated variance in mine water volumes and quality). The case study results indicate that treatment of saline mine water incurs a trade-off between water and energy use in all cases. However, significant cost differences between centralised and decentralised schemes can be observed in a simple economic analysis. Further research will examine the possibility for deriving model up-scaling algorithms to reduce computational requirements.

Exploring the impact of shared domain knowledge on strategic alignment in the Australian public sector

In this age of ever-increasing information technology (IT) driven environments, governments/or public sector organisations (PSOs) are expected to demonstrate the business value of the investment in IT and take advantage of the opportunities offered by technological advancements. Strategic alignment (SA) emerged as a mechanism to bridge the gap between business and IT missions, objectives, and plans in order to ensure value optimisation from investment in IT and enhance organisational performance. However, achieving and sustaining SA remains a challenge requiring even more agility nowadays to keep up with turbulent organisational environments. The shared domain knowledge (SDK) between the IT department and other diverse organisational groups is considered as one of the factors influencing the successful implementation of SA. However, SDK in PSOs has received relatively little empirical attention. This paper presents findings from a study which investigated the influence of SDK on SA within organisations in the Australian public sector. The developed research model examined the relationship of SDK between business and IT domains with SA using a survey of 56 public sector professionals and executives. A key research contribution is the empirical demonstration that increasing levels of SDK between IT and business groups leads to increased SA.

Using conservation evidence to guide management

Almost 10 years ago, Pullin and Knight (2001) called for an “effectiveness revolution in conservation” to be enabled by the systematic evaluation of evidence for conservation decision making. Drawing from the model used in clinicalmedicine, they outlined the concept of “evidencebased conservation” in which existing information, or evidence, from relevant and rigorous research is compiled and analyzed in a systematic manner to inform conservation actions (Cochrane 1972). The promise of evidencebased conservation has generated significant interest; 25 systematic reviews have been completed since 2004 and dozens are underway (Collaboration for Environmental Evidence 2010). However we argue that an “effectiveness revolution” (Pullin & Knight 2001) in conservation will not be possible unless mechanisms are devised for incorporating the growing evidence base into decision frameworks. For conservation professionals to accomplish the missions of their organizations they must demonstrate that their actions actually achieve objectives (Pullin & Knight 2009). Systematic evaluation provides a framework for objectively evaluating the effectiveness of actions. To leverage the benefit of these evaluations, we need resource-allocation systems that are responsive to their outcomes. The allocation of conservation resources is often the product of institutional priorities or reliance on intuition (Sutherland et al. 2004; Pullin & Knight 2005; Cook et al. 2010). We highlight the NICE technologyappraisal process because it provides an example of formal integration of systematic-evidence evaluation with provision of guidance for action. The transparent process, which clearly delineates costs and benefits of each alternative action, could also provide the public with new insight into the environmental effects of different decisions. This insight could stimulate a wider discussion about investment in conservation by demonstrating how changes in funding might affect the probability of achieving conservation objectives. ©2010 Society for Conservation Biology

Adaptive compliance control of a multi‐legged stair‐climbing robot based on proprioceptive data

Purpose – The purpose of this paper is to describe an innovative compliance control architecture for hybrid multi‐legged robots. The approach was verified on the hybrid legged‐wheeled robot ASGUARD, which was inspired by quadruped animals. The adaptive compliance controller allows the system to cope with a variety of stairs, very rough terrain, and is also able to move with high velocity on flat ground without changing the control parameters. Design/methodology/approach – The paper shows how this adaptivity results in a versatile controller for hybrid legged‐wheeled robots. For the locomotion control we use an adaptive model of motion pattern generators. The control approach takes into account the proprioceptive information of the torques, which are applied on the legs. The controller itself is embedded on a FPGA‐based, custom designed motor control board. An additional proprioceptive inclination feedback is used to make the same controller more robust in terms of stair‐climbing capabilities. Findings – The robot is well suited for disaster mitigation as well as for urban search and rescue missions, where it is often necessary to place sensors or cameras into dangerous or inaccessible areas to get a better situation awareness for the rescue personnel, before they enter a possibly dangerous area. A rugged, waterproof and dust‐proof corpus and the ability to swim are additional features of the robot. Originality/value – Contrary to existing approaches, a pre‐defined walking pattern for stair‐climbing was not used, but an adaptive approach based only on internal sensor information. In contrast to many other walking pattern based robots, the direct proprioceptive feedback was used in order to modify the internal control loop, thus adapting the compliance of each leg on‐line.

Fuzzy-DL perception for multi-robot systems

For future planetary robot missions, multi-robot-systems can be considered as a suitable platform to perform space mission faster and more reliable. In heterogeneous robot teams, each robot can have different abilities and sensor equipment. In this paper we describe a lunar demonstration scenario where a team of mobile robots explores an unknown area and identifies a set of objects belonging to a lunar infrastructure. Our robot team consists of two exploring scout robots and a mobile manipulator. The mission goal is to locate the objects within a certain area, to identify the objects, and to transport the objects to a base station. The robots have a different sensor setup and different capabilities. In order to classify parts of the lunar infrastructure, the robots have to share the knowledge about the objects. Based on the different sensing capabilities, several information modalities have to be shared and combined by the robots. In this work we propose an approach using spatial features and a fuzzy logic based reasoning for distributed object classification.