On Friday 22 July in a large exhibition hall in Brisbane, an innovative Queensland company, DanField Stratoship undertook a demonstration inflation of a stratospheric air ship.
The demonstration was organised by Trusted Autonomous Systems, a Defence Cooperative Research Centre in conjunction with the Royal Australian Air Force (RAAF) Air Warfare Centre (AWC), and as part of the groups involvement in the High-Altitude Pseudo Satellite (HAPS) Challenge.
The HAPS Challenge is exploring high altitude technologies including balloons that provide a range of lower-cost mechanisms to deploy payloads to areas of interest. Functions can include pseudo-satellite and persistent surveillance where reliable station-keeping and path-prediction functions are established. These technologies can provide lower cost, rapidly deployable capabilities for communications and surveillance tasks including bushfire early warning. HAPS Challenge management incorporates (Sir Lawrence Wackett Defence & Aerospace Centre – RMIT, SmartSat CRC, Trusted Autonomous Systems and RAAF Air Warfare Centre) supported by the Bureau of Meteorology.
The inflation demonstrates the technical status of the Stream 1 of the Challenge (Automated of Autonomous HAPS Platform Station Keeping & Constellation Maintenance) under the Power and Control in the Stratosphere (PACITS) project. This is currently in Phase 3, Prototype Development & Demonstration. PACITS is led by Danfield Stratoship and supported by a team The Stratoship Group including its sibling company Skysite, SuperSky Engineering, SmartSat Services and the Australian National University.
Ultimately, the conclusion on the Challenge will see a practical demonstration of the technology, deployed to the Stratosphere with regulatory approval processes underway.
Outstanding contributions to industry-led innovation and trust frameworks by Defence personnel have been recognised by Trusted Autonomous Systems (TAS) with six recipients receiving a 2022 Autonomy Accelerator Award.
The six recipients were individuals and teams who were nominated by TAS industry participants and TAS Project and Activity leads.
The Autonomy Accelerator Award recognises the significant contribution made by the recipient to the advancement of autonomous systems in Australia. Recipients have gone above and beyond to ensure delivery, displayed integrity, and been strongly committed to achieving shared goals.
Award recipients delivered on the TAS commitment to game-changing capability impact through industry projects and policy progress, which will ease pathways to deployment of trusted autonomous systems.
The recipients of the 2022 Autonomy Accelerator Awards are list below.
Program Leader LVC, Air & Space Program, DSTG
Robert serves as Program Leader LVC at DSTG, the latest in a series of leadership positions he has held there. Before migrating to Australia, he spent his career working for the US DoD, culminating in eight years at the Office of Naval Research Global, based in Japan and Chile. Before that he led the Asia-Pacific section at AFRL HQ, where he was charged with building and executing AFRL’s international engagement strategy for the Asia-Pacific region, and for developing collaborative research programs between AFRL and defence laboratories in the region. Prior to that he was a human factors scientist in the AFRL Human Effectiveness Directorate.
Robert was nominated for his science leadership and vision for building industry-led trusted autonomous systems as well as his commitment to building ethical frameworks suitable for Defence contexts of use. Robert has been a champion of TAS since inception in 2018, working collaboratively across organisations and stakeholder groups to increase sovereign capability for Australia. Robert’s commitment is evidenced in his co-authorship of ‘A Method for Ethical AI in Defence’ report by DSTG, RAAF and TAS leading to national and international policy impact including NATO and the TTCP AI Strategic Challenge.
Jared Freundt, George Katselis, Kris Allpress, Samuel Weckert, and Ian Lochert
Advanced Warhead Technologies Group, Weapons and Combat Systems Division, DSTG
Jared Freundt has over 20 years’ Defence Science and Technology experience focussed on characterising the performance of weapon system in support of Australian Defence Force requirements. Jared is a subject matter expert in high-speed photo instrumentation capability and has developed novel imaging techniques and analysis methods. In addition, he has developed a wide range of skills including; finite element analysis, explosive ordnance handling and safety and trial management. Due to his significant experience, he is currently working with the DSTG Trials Authority to ensure DSTG is well positioned for delivery of more complex trials into the future and to ensure they are managed consistently, safely and efficiently.
Jared Freundt and his team (George Katselis, Benjamin Hall, George Katselis, Kris Allpress, Samuel Wechert, Ian Lochert and others) in WSD were nominated for their exemplary collaboration with Skyborne Technologies on the Gannet Glide Drone program.
They produced a number of experimental warheads, which were tested successfully both in a standalone and integrated capacity. The collaboration resulted in an impressive demonstration at Port Wakefield in South Australia. Their efforts enabled a very successful outcome on all fronts.
Royal Australian Airforce; Artificial Intelligence Lead, Jericho Disruptive Innovation
Wing Commander Michael Gan commenced in his role as Deputy-Director Artificial Intelligence at Air Force’s Jericho Disruptive Innovation in September 2018. His previous experience in air mobility operations (particularly in humanitarian aid and disaster relief) as well as in critical thinking and ethics in professional military education has strongly influenced his approach to the development or Artificial Intelligence in the Royal Australian Air Force. His main focus has been on developing and exploring the AI foundations of education, ethics and assurance, while exploring Defence applications for computer vision and imagery analysis, natural language processing and AI/Data analytic decision support tools.
Michael Gan was nominated as a champion of industry-led innovation and his sustained commitment to building trusted sovereign capability in robotics, autonomous systems, and artificial intelligence. Michael ensures alignment of industry-led projects to Defence values in his ethical, legal and assurance of autonomy frameworks and tools exemplified in his co-authorship of ‘A Method for Ethical AI in Defence’ DSTG Technical Report by DSTG, RAAF and TAS leading to national and international policy impact including NATO and the TTCP AI Strategic Challenge.
Aerospace Division, DSTG
SQNLDR Morris has extensive RAAF Aircrew experience, primarily as an Airborne Electronics Officer and sensor employment specialist on P3-Orions, amassing around 7,500hrs. He also has UAS expertise from his involvement in the 2006, DSTG NW Shelf UAS trial. In 2010, he was selected as the Commanding Officer for the Heron UAS deployment to Afghanistan, (logging 400hrs). He has a wealth of experience in LOAC, Joint Fires, and Targeting from his time the Air and Space Operations Centre and HQJOC. SQNLDR Morris has been an Air Liaison Officer at DSTG since 2019 and with Human Factors group, in Aerospace Division since 2021.
The nomination recognised Robert (Bob) Morris for his excellent work in leading the HF assessments of Athena AI. From the time Bob came onboard, he worked directly with the engineering team to identify improvements to the capability, the training program and how evaluations would be conducted. Bob bought operational skills from decades of UAS experience in both theatre and T&E. He also supported liaison with RAAF and initial datasets for evaluation and integration. He worked directly with our engineering team to address roadblocks as they came up.
Upon conclusion of the project Bob Morris had conducted training and evaluation of Australia’s first AI enabled sensor to effector capability with 2 military units being 2SECFOR and 20STA, both of which were able to proficiently use the software within one day of training.
Professor, College of Science and Engineering, Flinders University
Professor Karl Sammut is a Co-Director of the Centre for Defence Engineering at Flinders University. Karl received his Ph.D from Nottingham University in 1992 before taking up positions at the Politecnico di Milano, followed by Loughborough University and then at Flinders University. Between 2019 and 2022, he held a part-time position as a Senior Principal Scientist with DSTG. Karl has over twenty years experience in maritime autonomy research for the development of uncrewed surface and underwater vehicles and has worked in collaboration with Trusted Autonomous Systems, DSTG, Thales, Boeing Australia, Lockheed Martin Australia, Naval Group and Fincantieri.
Karl was a key founding member of the team, and in concert with Thales and USYD helped put together the original proposal with Thales for the MCM in a day project. Karl and the Flinders team have been instrumental in driving the project forward from systems, software and hardware development perspective.
Karl is a driven and highly dependable member of the ‘MCM in a Day’ project. He has consistently supported and motivated the development of key software and hardware resources, despite a number of challenges. In doing so, he has enabled the progression of many key integration activities. He has regularly contributed solutions to numerous technical and administrative challenges throughout the duration of the project and has offered important insights and ideas that have notably furthered the project’s development. Karl’s efforts have demonstrably progressed project development, both within his immediate team at Flinders University and the project team as a whole.
Karl and Flinders team attendance at PAC was a great example of the commitment to project success that Karl fosters in the Flinders team, driving the Crawler and associated kit across from SA for the event in Sydney to ensure the teams would maximise their time to work on the equipment. Karl’s attitude and commitment influences the whole TAS MCM in a day project team in a hugely positive way.
Rafał Sienicki, Research Specialist
Information Sciences, Defence Science and Technology Group
Rafał (Ralph) joined DSTG in 2005. He has provided research, systems engineering and project management contributions to Defence projects in the areas of electronic warfare, radar and communication systems, distributed systems, and modelling, simulation, and experimentation. He is currently pursuing a PhD with the University of Sydney on deep learning approaches for spatial-temporal characterisation and prediction of the electromagnetic environment.
Ralph Sienicki has provided invaluable insights on the electromagnetic operating environment its characterization and effects, identified relevant research problems and applied creative solutions. Ralph has corralled DSTG effort toward Distributed aUtonomous Spectrum Management (DUST) milestones and goals, written high quality technical investigation reports, contributed constructively to DUST project reports and whilst the DSTG partner point of contact provided an exemplar of PM partner reports.
Ralph has facilitated productive exchanges and negotiations between DUST partners to bring project outcomes. Most recently Ralph has commenced a PhD aligned to the DUST project under the supervision of the DUST UoS partner.
About Trusted Autonomous Systems
Trusted Autonomous Systems (TAS) is Australia’s first Defence Cooperative Research Centre uniquely equipped to deliver research into world-leading autonomous and robotic technologies to enable trusted and effective cooperation between humans and machines. Funded by the Commonwealth via the Next Generation Technology Fund (NGTF) and the Queensland State Government, TAS aims to improve the competitiveness, productivity, and sustainability of Australian industry through industry-led projects with real translation opportunities to move technology rapidly from universities into industry and ultimately into leading edge capability for the Australian Defence Force. Projects are supported by ‘common-good’ activities in ethics, law and assurance of autonomy accelerating the operationalisation of capabilities. TAS is developing the capacity of Australia’s defence industry to acquire, deploy and sustain the most advanced autonomous and robotic technologies.
In a newly released series of videos on ethical AI, Trusted Autonomous Systems explores responsibility, governance, trust, law, and traceability for robotics, autonomous systems, and artificial intelligence.
These videos were produced by Trusted Autonomous Systems for the Centre for Defence Leadership & Ethics (CDLE) at the Australian Defence College.
The videos feature Chief Defence Science Prof Tanya Monro, ADF personnel, and representatives from Defence industries.
They explore topics of responsibility, governance, trust, law and traceability using a hypothetical science fiction scenario Striking Blind written by Australian Defence College Perry Group students in 2021. In the Striking Blind story, an Australian autonomy platform is deployed in a future operation with a fictional AI called ‘Mandela’.
The videos explore ethical and legal factors associated with this scenario. They highlight the need for maintaining robust oversight so that the ADF can benefit from AI and autonomous systems while addressing their complex challenges.
Designed for the full Defence learning continuum, the videos are based on the framework and pragmatic tools described in the Defence Science technical report A Method in Ethical AI in Defence (2021).
Using the framework the videos cover:
- Responsibility – who is responsible for AI?
- Governance – how is AI controlled?
- Trust – how can AI be trusted?
- Law – how can AI be used lawfully?
- Traceability – How are the actions of AI recorded?
- Pragmatic tools
While the method does not represent the views of the Australian Government, it provides an evidence-based collaborative framework relevant to Australian Defence contexts of use as well as ethical and legal considerations aligned with international best practice.
These videos provide both an overview and an in-depth exploration of A Method for Ethical AI in Defence and can be used within professional military education and by external stakeholders of Defence, including academia.
How to use the videos
- Use animations as thought prompts within presentations and workshops on robotics, autonomous systems, and artificial intelligence amongst Defence stakeholders.
- Use longer videos in a ‘flipped classroom’ model of learning for professional education and training
- Use videos in multi-stakeholder meetings to establish a shared framework within which to identify ethical and legal risks for robotics, autonomous systems and artificial intelligence projects for Defence
- Use pragmatic tools videos to establish processes for the identification and management of ethical and legal risks on RAS-AI projects
How to cite the videos
Producer Tara Roberson (Trusted Autonomous Systems)
Creative Director Kate Devitt (Trusted Autonomous Systems)
Publisher Trusted Autonomous Systems
Production Company Explanimate
Sponsor Centre for Defence Leadership & Ethics, Australian Defence College
With thanks to all interviewees who appeared in the videos: Stephen Bornstein, Damian Copeland, Kate Devitt, Michael Gan, Chris Hall, Sean Hamilton, Lachlan Jones, Rebecca Marlow, Tanya Monro AC, Mick Ryan AM, Lauren Sanders, Jason Scholz & Dominic Tracey.
Cite as: Roberson, T. & Devitt, S.K. (2022). Ethics of Robotics, Autonomous Systems and Artificial Intelligence Videos for Defence. [14 Videos] Trusted Autonomous Systems. https://tasdcrc.com.au/ethical-ai-defence-videos/
Demonstrating the viability of artificial intelligence (AI) requires thoughtful construction and communication of both social and technical aspects.
Demonstrations are both scientific experiments and social events designed around achieving buy-in for the technology. When it comes to AI, demonstrators face the challenge of conveying the smarts of the system and the role of human intent.
Two challenges of demonstrating the potential of AI are:
- Performing decision-making: working out how best to show cognitive and social decision making through complex autonomy demonstrations in a way that makes intelligent performance and errors understandable
- Showcasing ability to abide by human values and intent: working out how best to design a demonstration that shows the ability of a system to abide by decision making norms, including commander’s intent, military objectives, and ethical, legal, and safety-focused frameworks
Demonstrations are performances that include social and technical elements, such as: actors (humans, UI, software, networked systems and machines); enabling technologies (mechanics, comms, screens, instructions, consoles, connectivity, controls, batteries/fuel, security, lights, tents, generators); rituals (cultural behaviours, safety processes, signals); a choreographed narrative (CONOPS, narrative flow including objectives, cause and effect, conflict and emotions); planned, opportunistic and incidental interactions (stories, networking); evaluative criteria (expectations, key performance indicators); and goals (training/education, buy-in, positive emotions, media and communication outcomes, future investments, lessons learnt).
The TAS Ethics Uplift Program is conducting a research project that will develop and test an Autonomous Systems Demonstration Canvas to help optimise human understanding and buy-in for technology developers and investors. The Canvas will help tackle the opacity problem facing AI, for instance the way AI can obfuscate the rules, reasoning, and justifications underlying human-machine decision making as it occurs.
The first iteration of the ‘Autonomous Systems Demonstration Canvas’ V.1.1 (ASDC) was launched at the Queensland Defence Science Alliance (QDSA) Human Teaming and Response Robotics Standardised Testing, Evaluation and Certification Interactive Showcase at CSIRO’s Queensland Centre for Advanced Technologies’ MILTECS facilities on 21 April 2022.
The Canvas provides a scaffolding framework to help technology developers efficiently prepare, practise, and perform impactful technology demonstrations to diverse stakeholders to achieve diverse goals including attracting investment, showing technical progress, and getting publicity.
The intention is for the Canvas to inform future trials as a tool to support impactful demonstration planning for TAS programs. For more information on the Autonomous Systems Demonstration Canvas contact Dr Kate Devitt email@example.com.
By Rachel Horne, Assurance of Autonomy Activity Lead, TAS
Trusted Autonomous Systems (TAS) has released the Australian Code of Practice for the Design, Construction, Survey and Operation of Autonomous & Remotely Operated Vessels, Edition 1 (‘Australian Code of Practice’).
The Australian Code of Practice provides a best practice standard tailored for autonomous and remotely operated vessels operating in Australia. It is a voluntary standard, developed in close consultation with the Australian Maritime Safety Authority (AMSA), intended to be used to support assurance, accreditation, and safe operations.
The development of the Australian Code of Practice was informed by an analysis of existing, publicly available codes and guidelines for autonomous and remotely operated vessels, significant stakeholder engagement, and public consultation.
TAS, supported by Australian Maritime College Search, have also developed a suite of Guidance Materials to support the use of the Australian Code of Practice. These Guidance Materials explain how the Australian Code of Practice fits into the existing Australian maritime regulatory framework, how to use the Code, and what the requirements are for each category of vessel, together with providing examples and suggestions on where to access further information.
TAS encourages owners, operators, surveyors, regulators and other users of the Australian Code of Practice and Guidance Materials to provide feedback to TAS, to help inform future iterations.
Where can I get more information?
To access more information on the Australian Code of Practice, you can:
- Download Edition 1 of the Australian Code of Practice and Guidance Materials
- Download the Public Consultation Report
- View previous TAS website articles on this project:
- New TAS project to develop an Australian Code of Practice for the Design, Construction, Survey and Operation of Autonomous and Remotely Operated Vessels in 2021
- Outcomes of successful webinar on TAS’s project to develop an Australian Code of Practice for the Design, Construction, Survey and Operation of Autonomous & Remotely Operated Vessels in 2021
- TAS Report: Analysis of available standards and codes for autonomous and remotely operated vessels
- Enabling COLREGs compliance for autonomous & remotely operated vessels
- Public consultation commences on draft Australian Code of Practice for the Design, Construction, Survey and Operation of Autonomous & Remotely Operated Vessels
- Email us at firstname.lastname@example.org
TAS would like to thank all parties who contributed to the development of the Australian Code of Practice, including particularly Maaike Vanderkooi of Vanderkooi Consulting who led the development of the Code on TAS’s behalf, Rob Dickie of Frazer Nash Consultancy who led the COLREGs project on TAS’s behalf, together with his team Marceline Overduin and Andrejs Jaudzems, and Chris White from AMC Search who led delivery of the Guidance Materials, together with his team Reuben Kent, Damien Guihen, and Nick Bonser.
This project received funding support from the Queensland Government through Trusted Autonomous Systems (TAS), a Defence Cooperative Research Centre funded through the Commonwealth Next Generation Technologies Fund and the Queensland Government.
 UK Code of Practice for Maritime Autonomous Surface Ships, the LR Code for Unmanned Marine Systems, and DNV GL’s Autonomous and Remotely-operated Ships Class Guideline
By Rachel Horne, Assurance of Autonomy Activity Lead, TAS
TAS and Frazer-Nash Consultancy have developed a COLREGs Operator Guidance Framework to make it easier to understand and comply with International Regulations for Preventing Collisions at Sea (COLREGs) when operating autonomous and remotely operated vessels. This Framework is available for standalone use, or as an annex to the new Australian Code of Practice for the Design, Construction, Survey and Operation of Autonomous and Remotely Operated Vessels.
The COLREGs Operator Guidance Framework translates the stated and unstated capabilities described, and the terminology used, in COLREGs into a vocabulary and format that makes sense for autonomous and remotely operated vessels. It is intended to be an enabling framework to:
- Help vessel designers understand what capabilities COLREGs requires vessels to have;
- Help operators understand what capabilities COLREGs requires and how mission planning can mitigate or remove the need for solving some of the more complex elements of COLREGs; and
- Help regulators apply a consistent methodology for assessing the capability of a vessel with regards to COLREGs.
The intent is that the information gathered using the COLREGs Operator Guidance Framework will be used to inform regulatory approval processes and operational planning.
The COLREGs Operator Guidance Framework is currently presented as a PDF, which is best used printed in A3. It is also being converted to a digital tool in a collaboration between TAS, Frazer-Nash, and Aginic over the coming months.
Using the COLREGs Operator Guidance Framework
The recommended use of the COLREGs Operator Guidance Framework for an operator with a specific vessel and proposed operation in mind is as follows:
- Download and print out the COLREGs Operator Guidance Framework in A3 colour
- Download and fill out the Design Record Template, to ensure you have documented the capabilities of your vessel
- With your vessel particulars and the details of your proposed operation in mind, review the framework document, reading from left to right, and identify:
- When each rule in COLREGs applies (i.e. some only apply in specific contexts like when in Narrow Channels)
- The capabilities required to comply with each specific rule, broken down into the categories of Sense and Perceive, Decide, and Act (noting that these could be in the vessel, the control centre, or a combination)
- Mission constraints that could be implemented if you don’t have the capabilities to comply with a specific rule, to remain in compliance (for example, if you don’t have the capabilities needed to comply with Rule 9 – Narrow Channels, you may plan to avoid narrow channels, and therefore remain in compliance with COLREGs)
- The suitable method of compliance for each rule (for example, for Rule 5 – Lookout, the proposed evidence of compliance is Design Checklist and Simulation)
- Review your analysis, and prepare for own records a list of applicable rules for your vessel and proposed operation, corresponding required capabilities, any operational limitations that need to be imposed, and the recommended evidence type. You may then wish to provide your filled out Design Record and your analysis against the COLREGs Operator Guidance Framework to AMSA to support your application for exemption and/or certification. You can also review it when conducting operational planning to ensure you remain COLREGs compliant.
Further guidance materials, examples, and an instructional video will be released to support the use of the COLREGs Operator Guidance Framework in the coming months.
Background information on the project to develop the COLREGs Operator Guidance Framework, including the process the team used, is made available in a Briefing Note prepared by Frazer-Nash.
TAS will be working with Frazer-Nash and Aginic to develop a digital version of the COLREGs Operator Guidance Framework. TAS intends to make this digital version available through RAS-GATEWAY, a new online portal for assurance and accreditation information and support for autonomous and remotely operated vessels.
The TAS RAS-Gateway project is creating a digital hub to support the Australian autonomous systems sector, including operators and the testing and evaluation ecosystem. The Gateway will feature new methods, policies, practices, and expertise to support accreditation. It aims to address issues currently experienced by regulators, insurers, and technology developers by, for instance, filling gaps in standards and producing consistent (yet flexible) parameters for safe and trusted operations and improved agility to meet fast-changing technical and social licence needs.
In parallel with this digital development, the COLREGs Operator Guidance Framework will be tested through a trial at the Reefworks testing range in Townsville later in 2022.
TAS welcomes feedback on the COLREGs Operator Guidance Framework to email@example.com
TAS would like to thank all parties who contributed to the development of the COLREGs Operator Guidance Framework, including particularly Rob Dickie, Marceline Overduin and Andrejs Jaudzems of Frazer-Nash Consultancy for their smarts and creativity in identifying the best way to turn an idea into a tangible enabling framework, and then doing the hard analytical, excel, and design work to make it happen.
This project received funding support from the Queensland Government through Trusted Autonomous Systems (TAS), a Defence Cooperative Research Centre funded through the Commonwealth Next Generation Technologies Fund and the Queensland Government.
By Rachel Horne, Assurance of Autonomy Activity Lead, TAS
Public consultation occurred on the draft Australian Code of Practice for the Design, Construction, Survey and Operation of Autonomous & Remotely Operated Vessels, (‘Australian Code of Practice’) between 15 November 2021 and 15 December 2021.
Background information on the development of the Australian Code of Practice and the public consultation process is available on the TAS website.
TAS received seven written submissions from a diverse range of stakeholders, include SMEs developing vessels, government departments and Recognised Organisations. TAS thanks all stakeholders for taking the time to review the draft Code and make submissions.
The submissions received were considered, and further advice was sought from third parties assisting with the project where needed, to determine where changes were required to the Code. Examples of the changes made to the Code post-consultation include:
- the accuracy of sensors is now required to be determined and declared, and their performance is required to be monitored. This will help to ensure that vessels do not operate in conditions where the sensors are not sufficiently effective, or when sensors cease to be sufficiently effective;
- the control system must now be able to be disabled and isolated to allow for inspection and maintenance activities;
- for survey-exempt vessels and vessels in survey, the risk assessment of any novel system must now be reviewed by an accredited marine surveyor or Recognised Organisation. A note has been added which provides that review by a competent person may be sufficient for a survey-exempt vessels where the vessel, due to its size, speed and shape, poses a very low risk to the safety of persons and other vessels should a failure occur;
- for survey-exempt vessels and vessels in survey, tests or trials must now be witnessed by an accredited marine surveyor or Recognised Organisation. A note has been added which provides that a competent person witnesses the tests or trials may be sufficient for a survey-exempt vessels where the vessel, due to its size, speed and shape, poses a very low risk to the safety of persons and other vessels should a failure occur; and
- improved alignment of the Code with the AMSA Guidance Notice – Small unmanned autonomous vessels, including changing the guidance on the operational speed permitted for survey-exempt vessels from 12 knots to 10 knots.
A Consultation Feedback Report was prepared which summarises the consultation undertaken, the responses received, and the outcomes.
Once the necessary changes were made to the Code, the updated draft was provided back to AMSA for further review, before confirming it was ready to be finalised as Edition 1.
TAS welcomes ongoing feedback from users of the Code, which will support further future iterations and improvements.
For further information please contact us at firstname.lastname@example.org.
Through disruptive innovation, Warfare Innovation Navy (WIN) Branch enables the Royal Australian Navy to be at the forefront of asymmetric warfighting for joint integrated effects. The iDrogue project, initiated by Trusted Autonomous Systems, led by Ocius Technology, and funded by WIN Branch, was established to develop and demonstrate a novel Autonomous Underwater Vessel (AUV) launch and recovery system. Ocius, a leading Australian innovator, is partnered with the Australian Maritime College and University of New South Wales on this exciting project. This pilot project is being conducted over 12-months, through 2022.
- The ultimate aim, with further funding, is to develop an intelligent robot based on biomimicry that can launch and recover ‘any AUV, from any platform in virtually any sea state’.
- AUVs are in increasing use by modern navies. The current method of launching and recovering AUVs is undertaken by humans at the sea surface level.
- This pilot program will exploit advanced robotics and autonomy to undertake functions at calm depth and without human involvement. In the next 6-months the iDrogue will be automated and the design reviewed.
- This project contributes to RAN sea superiority with a capability that integrates with current and future fleets and allied capabilities.
- The graphics on the stand represent human machine teaming and human control.
- It is an industry led (Ocius) project funded by WIN Branch and overseen through Trusted Autonomous Systems.
- Ocius partners include AMC Search, UNSW and Southern Ocean Subsea (SOSUB).
- WIN – Through disruptive innovation, Warfare Innovation Navy (WIN) Branch enables the Royal Australian Navy to be at the forefront of asymmetric warfighting for joint integrated effects.
- Ocius Technology have developed a range of uncrewed platforms. More on their range is available here.
- Trusted Autonomous Systems (TAS) were established though the Next Generation Technologies Fund (NGTF) to accelerate autonomous systems development for Defence. The TAS vision is ‘Smart, small & many’ and projects cover all domains.
Queensland’s robotics, artificial intelligence and autonomous systems sector has been boosted thanks to significant funding from the state government.
The Advance Queensland – Trusted Autonomous Systems (TAS) grant has been awarded to three game-changing and researched-backed projects.
These industry-led projects will increase the state’s capacity to build robotics, autonomous systems and artificial intelligence hardware and software.
Two of the projects involve the preservation of cultural art and language in Indigenous communities in north Queensland.
TAS CEO Professor Jason Scholz said its ongoing partnership with the state government highlighted both organisations’ continued leadership in drone and AI technology to grow small businesses in regional areas.
Professor Scholz said, “TAS and Advance Queensland is investing in RAS-AI projects with industry, non-profit organisations and universities to develop data and AI project methodologies for secure and trusted AI.”
TAS Chief Scientist Dr Kate Devitt said, “The technologies and methods developed, as well as the AI governance mechanisms applied, would place the state at the forefront of international best practice.”
The first project, led by KJR with the Western Yalanji Aboriginal Corporation, will work on human-machine teaming to identify and protect high-value cultural assets. Other partners on the project are Athena AI, Emesent, Flyfreely, MaxusAI, the Australian National University, University of Queensland, and Griffith University.
The second project is a collaboration between Revolution Aerospace and the Queensland University of Technology. The team will work on a low-cost cognitive electronic system hosted on an Uncrewed Aerial Vehicle (UAV).
The third project from Pama Language Centre and the University of Queensland, will focus on developing AI and automation in language technologies, with speech communities and providing training.
The grants were awarded after an extensive competitive process. Each will run for two years, until December 2023.
Human-machine teaming to identify and protect high value cultural assets
KJR and partners (Western Yalanji Aboriginal Corporation, Athena AI, Emesent, Flyfreely, MaxusAI, World of Drones Education Pty Ltd, and Griffith University) will develop a secure multi-platform human-machine teaming capability in Queensland through using semi-autonomous drones for data capture and machine learning for image classification to identify and protect Western Yalanji rock art.
Cognitive Payloads for Small UAV
Revolution Aerospace and Queensland University of Technology are teaming with Queensland University of Technology (QUT) to build a low-cost cognitive electronic system hosted on an Uncrewed Aerial Vehicle (UAV).
AI and automation in language technologies: securing Queensland’s data sovereignty.
Pama Language Centre (PLC) and Janet Wiles, Ben Foley, and Ben Matthews at UQ will collaborate on a series of projects with speech communities. They will be designing, developing and evaluating new language technologies including a digital asset manager for language resources, tools to support sharing of augmented reality assets, and workshops to build capacity and resource creation. It will also extend the ARC Centre of Excellence for the Dynamics of Language (CoEDL) Transcription Acceleration Project (TAP) application of ‘transfer learning’ for speech recognition, aimed at reducing the training data and time needed to develop novel speech recognition systems. An example of an existing PLC project utilising Augmented Reality is available here.
Building QLD capability
The industry-led projects will build robotics, autonomous systems and artificial intelligence hardware and software. They will achieve:
- Transdisciplinary research impact and sovereign capability in smart, resilient, and deployable systems in congested and variable data environments.
- Next generation AI/Machine Learning (ML) methods and apply research into deployable systems
- New models of data governance, data sovereignty, and assurance of ML pipelines
- Technology integration to build trusted autonomy
- Best practice ethical AI through participatory design
- Digital regulatory approvals
Outputs from the projects will include:
- AI Integration, augmented reality, advanced signal processing, AI classifier acceleration, AI language technologies, AI to aid in preserving cultural assets, and education materials/programs to train regional workers in use of next gen technologies
- AI for Sovereign capability, Defence and regional Queensland communities
- Technologies, frameworks, and methodologies developed in these projects are applicable to Defence AI and autonomy requirements as per the 2020 Strategic Update and Defence Data Strategy 2021-2023.