ORCID Profile
0000-0003-0806-7720
Current Organisations
Warith International Cancer Institute
,
Queensland University of Technology (QUT)
,
Queensland University of Technology
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Environmental Engineering not elsewhere classified | Interdisciplinary Engineering not elsewhere classified | Environmental Engineering | Environmental Monitoring | Adaptive Agents and Intelligent Robotics | Other Biological Sciences | Atmospheric Sciences | Environmental Management | Artificial Intelligence and Image Processing | Public Health and Health Services not elsewhere classified | Atmospheric Sciences not elsewhere classified | Computer Vision | Climate Change Processes | Global Change Biology
ANZSRC Socio-Economic Objective (SEO)
Environmental Health | Air Quality not elsewhere classified | Effects of Climate Change and Variability on Antarctic and Sub-Antarctic Environments (excl. Social Impacts) | Plant Production and Plant Primary Products not elsewhere classified | Ecosystem Assessment and Management of Antarctic and Sub-Antarctic Environments | Environmental Policy, Legislation and Standards not elsewhere classified | Computer Software and Services not elsewhere classified | Manufacturing not elsewhere classified | Ground Transport not elsewhere classified |
Related Links
Publications
Adaptive receding horizon control for a high-speed autonomous surface vehicle in narrow waterways
Publisher: IEEE
Date: 08-2017
The Tasmanian Marine Analysis Network (TasMAN)
Publisher: IEEE
Date: 05-2009
Vision-based docking using an autonomous surface vehicle
Publisher: IEEE
Date: 05-2008
Experimental evaluation of an Autonomous Surface Vehicle for water quality and greenhouse gas emission monitoring
Publisher: IEEE
Date: 05-2010
Robots for Environmental Monitoring: Significant Advancements and Applications
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2012
Automatic Wildfire Detection and Simulation using Optical Information from Unmanned Aerial Systems
Publisher: SAE International
Date: 15-09-2015
DOI: 10.4271/2015-01-2474
A Hybrid AUV Design for Shallow Water Reef Navigation
Publisher: IEEE
Date: 2005
The importance of small artificial water bodies as sources of methane emissions in Queensland, Australia
Publisher: Copernicus GmbH
Date: 15-10-2018
DOI: 10.5194/HESS-22-5281-2018
Abstract: Abstract. Emissions from flooded land represent a direct source of anthropogenic greenhouse gas (GHG) emissions. Methane emissions from large, artificial water bodies have previously been considered, with numerous studies assessing emission rates and relatively simple procedures available to determine their surface area and generate upscaled emissions estimates. In contrast, the role of small artificial water bodies (ponds) is very poorly quantified, and estimation of emissions is constrained both by a lack of data on their spatial extent and a scarcity of direct flux measurements. In this study, we quantified the total surface area of water bodies 105 m2 across Queensland, Australia, and emission rates from a variety of water body types and size classes. We found that the omission of small ponds from current official land use data has led to an underestimate of total flooded land area by 24 %, of small artificial water body surface area by 57 % and of the total number of artificial water bodies by 1 order of magnitude. All studied ponds were significant hotspots of methane production, dominated by ebullition (bubble) emissions. Two scaling approaches were developed with one based on pond primary use (stock watering, irrigation and urban lakes) and the other using size class. Both approaches indicated that ponds in Queensland alone emit over 1.6 Mt CO2 eq. yr−1, equivalent to 10 % of the state's entire land use, land use change and forestry sector emissions. With limited data from other regions suggesting similarly large numbers of ponds, high emissions per unit area and under-reporting of spatial extent, we conclude that small artificial water bodies may be a globally important missing source of anthropogenic greenhouse gas emissions.
Quantifying Spatiotemporal Greenhouse Gas Emissions Using Autonomous Surface Vehicles
Publisher: Wiley
Date: 22-07-2016
DOI: 10.1002/ROB.21665
Exploring the “Sharkcano”: Biogeochemical Observations of the Kavachi Submarine Volcano (Solomon Islands)
Publisher: The Oceanography Society
Date: 12-2016
A framework for marine sensor network & autonomous vehicle interaction
Publisher: IEEE
Date: 05-2010
Automated Counting of the Northern Pacific Sea Star in the Derwent Using Shape Recognition
Publisher: IEEE
Date: 12-2007
Autonomous excavation using a rope shovel
Publisher: Wiley
Date: 06-2006
DOI: 10.1002/ROB.20132
Abstract: This paper describes the development of a system to automate the digging cycle of an electric rope shovel, a machine which is widely used in open‐pit mining. Achieving optimal digging performance requires path planning strategies to ensure dipper (bucket) filling, as well as methods to detect when to disengage the dipper from the bank. To this end, techniques to detect and avert dipper stall, and the online estimation of dipper “full‐ness,” are described along with in‐field experimental results using a one‐seventh scale‐model electric rope shovel. Over 100 autonomous excavation cycles, in a variety of digging conditions, resulted in cycle times consistent with a human operator, but with lower overall motor loading. © 2006 Wiley Periodicals, Inc.
Multimodal Sensor Fusion for Robust Obstacle Detection and Classification in the Maritime RobotX Challenge
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Experiments with Cooperative Control of Underwater Robots
Publisher: SAGE Publications
Date: 20-05-2009
Abstract: In this paper we describe cooperative control algorithms for robots and sensor nodes in an underwater environment. Cooperative navigation is defined as the ability of a coupled system of autonomous robots to pool their resources to achieve long-distance navigation and a larger controllability space. Other types of useful cooperation in underwater environments include: exchange of information such as data download and retasking cooperative localization and tracking and physical connection (docking) for tasks such as deployment of underwater sensor networks, collection of nodes and rescue of damaged robots. We present experimental results obtained with an underwater system that consists of two very different robots and a number of sensor network modules. We present the hardware and software architecture of this underwater system. We then describe various interactions between the robots and sensor nodes and between the two robots, including cooperative navigation. Finally, we describe our experiments with this underwater system and present data.
Data muling over underwater wireless sensor networks using an autonomous underwater vehicle
Publisher: IEEE
Date: 2006
Importance of sediment organic matter to methane ebullition in a sub-tropical freshwater reservoir
Publisher: Elsevier BV
Date: 04-2018
DOI: 10.1016/J.SCITOTENV.2017.10.108
Abstract: This paper summarises the results of an extensive field c aign which demonstrates that high sediment organic matter is the primary driver of methane ebullition in a sub-tropical, freshwater reservoir. Methane emissions from freshwater reservoirs represent an important global methane source. Whilst diffusive methane fluxes are commonly used for predicting total emissions, recent studies show that the under-reported ebullitive fluxes can vary by over three orders of magnitude within an in idual system and have a greater relative contribution compared to diffusion. Key to predicting this variability in emission rates is to better understand the primary drivers of different emission pathways, and in particular ebullition. Zones of catchment derived organic material as well as elevated water column chlorophyll a concentration have been associated with increased rates of ebullition. Little Nerang Dam (LND), a subtropical freshwater reservoir in Queensland Australia, consistently experiences high rates of ebullition adjacent to major inflow arms that are both deposition zones of catchment organic material as well as areas with elevated water column chlorophyll a concentration. A year-long study of emission rates was undertaken on LND during which water column chlorophyll a concentration, bottom water temperature and sediment organic matter content were assessed for methane ebullition potential. This included a transect with high-spatial s ling (259 sites) from the dam wall to the ebullition zones to explore the relationship between water column chlorophyll a concentration, sediment organic matter content and methane ebullition. These results showed that ebullition was associated with the large forest litter deposits adjacent to major inflow sites where sediment organic matter content was significantly higher compared with the main body of the reservoir.
Exercise-induced hypoxia secondary to an atrial septal defect and cor triatriatum dexter
Publisher: Cambridge University Press (CUP)
Date: 30-09-2015
DOI: 10.1017/S1047951115001870
Abstract: A 14-year-old boy presented to us with a diagnosis of severe asthma and oxygen desaturation of 76% on a 6-minute-walk test. A contrast echocardiogram revealed echocontrast in the left and right atria simultaneously. A secundum atrial septal defect and partial cor triatriatum dexter were diagnosed, and the atrial defect was closed by cardiac catheterisation.
Krill: An Exploration in Underwater Sensor Networks
Publisher: IEEE
Date: 2005
Experiments with Underwater Robot Localization and Tracking
Publisher: IEEE
Date: 04-2007
Visual Motion Estimation for an Autonomous Underwater Reef Monitoring Robot
Publisher: Springer Berlin Heidelberg
Date: 2006
Experiments with Cooperative Networked Control of Underwater Robots
Publisher: Springer Berlin Heidelberg
Date: 2008
Autonomous Excavation Using a Rope Shovel
Publisher: Springer Berlin Heidelberg
Date: 2006
Autonomous Greenhouse Gas Sampling Using Multiple Robotic Boats
Publisher: Springer International Publishing
Date: 2016
Data collection, storage, and retrieval with an underwater sensor network
Publisher: ACM
Date: 02-11-2005
Simultaneous underwater visibility assessment, enhancement and improved stereo
Publisher: IEEE
Date: 05-2014
An international survey of imaging practices in radiotherapy
Publisher: Elsevier BV
Date: 10-2021
Field and service applications - Dragline automation- A dedade of development - Shared Autonomy for Improving Mining Equipment Productivity
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2007
Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?
Publisher: Elsevier BV
Date: 07-2018
Integrating field survey data with satellite image data to improve shallow water seagrass maps: the role of AUV and snorkeller surveys?
Publisher: Informa UK Limited
Date: 02-2015
Adaptable Distributed Sensing in Coastal Waters: Design and Performance of the μFloat System
Publisher: Field Robotics Publication Society
Date: 10-01-2023
DOI: 10.55417/FR.2023016
Abstract: Buoyancy-controlled underwater floats have produced a wealth of in situ observational data from the open ocean. When deployed in large numbers, or “distributed arrays,” floats offer a unique capacity to concurrently map 3D fields of critical environmental variables, such as currents, temperatures, and dissolved oxygen. This sensing paradigm is equally relevant in coastal waters, yet it remains underutilized due to economic and technical limitations of existing platforms. To address this gap, we developed an array of 25 μFloats that can actuate vertically in the water column by controlling their buoyancy, but are otherwise Lagrangian. Underwater positioning is achieved by acoustic localization using low-bandwidth communication with GPS-equipped surface buoys. The μFloat features a high-volume buoyancy engine that provides a 9% density change, enabling automatic ballasting and vertical control from fresh to salt water ( 3% density change) with reserve capacity for external sensors. In this paper, we present design specifications and field benchmarks for buoyancy control and acoustic localization accuracy. Results demonstrate depthholding accuracy within ±0.2 m of target depth in quiescent flow and ±0.5 m in energetic flows. Underwater localization is accurate to within ±5 m during periods with sufficient connectivity, with degradation in performance resulting from adverse sound speed gradients and unfavorable spatial distributions of surface buoys. Support for auxiliary sensors ( % float volume) without additional control tuning is also demonstrated. Overall performance is discussed in the context of potential use cases and demonstrated in a first-ever array-based three-dimensional survey of tidal currents.
High-Fidelity Autonomous Surface Vehicle Simulator for the Maritime RobotX Challenge
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Robust vision‐based underwater homing using self‐similar landmarks
Publisher: Wiley
Date: 06-2008
DOI: 10.1002/ROB.20246
Abstract: Next‐generation autonomous underwater vehicles (AUVs) will be required to robustly identify underwater targets for tasks such as inspection, localization, and docking. Given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods however, reliable target segmentation often plagues these systems. This paper addresses robust vision‐based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on self‐similar landmarks that enables robust target pose estimation with respect to a single camera. These algorithms are applied to an AUV with controllers developed for vision‐based docking with the target. Experimental results show that the system performs exceptionally on limited processing power and demonstrates how the combined vision and controller system enables robust target identification and docking in a variety of operating conditions. © 2008 Wiley Periodicals, Inc.
Robotics for Environmental Monitoring [From the Guest Editors]
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2012
Quantification of ebullitive and diffusive methane release to atmosphere from a water storage
Publisher: Elsevier BV
Date: 12-2011
Predictive motion planning for AUVs subject to strong time-varying currents and forecasting uncertainties
Publisher: IEEE
Date: 05-2015
An RPC-Based Service Framework for Robot and Sensor Network Integration
Publisher: IEEE
Date: 05-2011
Modular field robot deployment for inspection of dilapidated buildings
Publisher: Wiley
Date: 30-04-2019
DOI: 10.1002/ROB.21872
A shallow water AUV for benthic and water column observations
Publisher: IEEE
Date: 05-2015
LunaRoo: Designing a hopping lunar science payload
Publisher: IEEE
Date: 03-2016
Uncrewed autonomous marine vessels test the limits of maritime safety frameworks
Publisher: Springer Science and Business Media LLC
Date: 19-12-2022
DOI: 10.1007/S13437-022-00295-X
Abstract: Uncrewed and autonomous marine vessels (UMVs) challenge the underlying paradigm of maritime laws and regulations. Yet UMVs are considered essential for safer, more efficient, and more effective maritime futures. There is a fundamental challenge facing industry and regulators about how to develop and support the nascent UMV industry while maintaining the safety and risk management principles and processes in legacy laws and regulations predicated on the conventional crewed vessel. This paper, drawing upon case studies of developer and operator experiences with Australia’s maritime safety framework, argues for an “intent-based”, flexible, and collaborative approach based on developers’ and operators’ experiences. The case studies show that ad hoc and bespoke regulatory pathways, utilising exemptions and discretions under Australian national laws, although problematic in terms of regulatory consistency and capacity to deal with scale, did allow for the trialling and deployment of two small UMVs. More importantly, the ad hoc approach facilitated information exchange between industry and regulators that is generating reforms and changes at the national level. Although focused on Australia, the findings are significant for maritime futures. It reveals a dialectical approach whereby maritime nations pragmatically work through the risks, standards, and processes that balance safety with facilitating local UMV industries, and in turn, this creates a body of knowledge to inform international reform processes. It also shows the importance of documenting and reflecting on the regulatory journeys of UMV pioneers as essential for safer, more efficient, and effective maritime industries that leverage the potential benefits of automation.
Robotic detection and tracking of Crown-of-Thorns starfish
Publisher: IEEE
Date: 09-2015
Dragline Automation: Experimental Evaluation through Productivity Trial
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/10991459_44
Mobile phones as monitors of personal exposure to air pollution: Is this the future?
Publisher: Public Library of Science (PLoS)
Date: 23-02-2018
Robust Vision-Based Underwater Target Identification and Homing Using Self-Similar Landmarks
Publisher: Springer Berlin Heidelberg
Date: 2008
Related Organisations
Commonwealth Scientific And Industrial Research Organisation
Location: Australia
Related Funding Activities
Revolutionising Protection Against Air Pollution
Start Date: 2015
End Date: 2017
Funder: Australian Research Council
View Funded ActivityEstablishing Advanced Networks For Air Quality Sensing And Analyses
Start Date: 2016
End Date: 2018
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP180100516
Start Date: 12-2019
End Date: 12-2023
Amount: $889,797.00
Funder: Australian Research Council
View Funded ActivityDiscovery Projects - Grant ID: DP150101828
Start Date: 02-2015
End Date: 12-2018
Amount: $315,778.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP160100051
Start Date: 04-2017
End Date: 04-2020
Amount: $445,000.00
Funder: Australian Research Council
View Funded ActivityARC Centres Of Excellence - Grant ID: CE140100016
Start Date: 07-2014
End Date: 03-2021
Amount: $19,000,000.00
Funder: Australian Research Council
View Funded ActivitySpecial Research Initiatives - Grant ID: SR200100005
Start Date: 06-2021
End Date: 06-2030
Amount: $36,000,000.00
Funder: Australian Research Council
View Funded Activity