Degree type
PhD
Closing date
1 June 2024
Campus
Hobart
Citizenship requirement
Domestic
About the research project
Large-scale seafloor monitoring is generally done through Autonomous underwater vehicles (AUVs) which can go in depths of ocean and collect highly detailed acoustic and optical images [1]. These vehicles execute pre-determined mission plans. The key issue faced is how to make real time operational decisions regarding sensor controls, vehicle parameters such as altitude, or mission plan adaptation. Currently, due to very low network bandwidth, these decisions cannot be done until all data is retrieved and then analysed [2]. The amount of data collected is very large; which deter any quick decision making. Moreover, it is quite expansive to deploy these AUVS for testing.
Therefore, an intelligent system is needed to improve the effectiveness of monitoring during the mission. However, existing AI models may have also limited accuracy due to dynamic nature of the problem with inefficient processing power. Moreover, onboard decision making needs to be aggregated with other processing devices with limited communication. These challenges are not trivial as algorithm testing cannot be conducted with real AUVs. This necessitates development of novel simulation framework where distributed AI methods can be tested and provide results equivalent to real situation.
This project aims to apply distributed system and AI principles [3] to investigate a novel simulation based distributed AI models that will enable testing and development of decision making algorithms for enabling near-real time maneuvering of AUVs for ocean surveillance. In this project, on-board and off-line smart analysis distributed AI algorithms will be developed to select and recommend best mission plan in real time depending on the environmental and seafloor conditions.
1. Molina-Molina, J. Carlos, et al. "Autonomous marine robot based on AI recognition for permanent surveillance in marine protected areas." Sensors 21.8 (2021): 2664.
2. Zhou, Mingxi, and Jianguang Shi. "An Uncertainty-driven Sampling-based Online Coverage Path Planner for Seabed Mapping using Marine Robots." 2022 IEEE/OES Autonomous Underwater Vehicles Symposium (AUV). IEEE, 2022.
3. Chaib-draa, Brahim. "Industrial applications of distributed AI." Communications of the ACM 38.11 (1995): 49-53.
Primary Supervisor
Meet Saurabh GargFunding
Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:
- a living allowance stipend of $32,192 per annum (2024 rate, indexed annually) for 3.5 years
- a relocation allowance of up to $2,000
- a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)
If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.
As part of the application process you may indicate if you do not wish to be considered for scholarship funding.
Other funding opportunities and fees
For further information regarding other scholarships on offer, and the various fees of undertaking a research degree, please visit our Scholarships and fees on research degrees page.
Eligibility
Applicants should review the Higher Degree by Research minimum entry requirements.
Ensure your eligibility for the scholarship round by referring to our Key Dates.
Additional eligibility criteria specific to this project/scholarship:
- Applicants must be able to undertake the project on-campus.
Selection Criteria
The project is competitively assessed and awarded. Selection is based on academic merit and suitability to the project as determined by the College.
Additional essential selection criteria specific to this project:
Research Experience in -
- Distributed Computing
- Artificial Intelligence
Application process
- Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
- Contact Saurabh Garg to discuss your suitability and the project's requirements; and
- In your application:
- Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
- Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
- Apply prior to 1 June 2024.
Full details of the application process can be found under the 'How to apply' section of the Research Degrees website.
Following the closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.
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