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A quarterly newsletter from the QUT Centre for Robotics
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Welcome to the first newsletter from the QUT Centre for Robotics. This is a quarterly catch-up about what’s been going on at the Centre. 
Feel free to forward this to your colleagues and they can use this opt-in link http://eepurl.com/hIKu8z to subscribe and get their own copy in future. You can find out more about us at any time by visiting our website at qcr.ai or check out our new promo video.
The QUT Centre for Robotics (QCR) was established at the beginning of 2020 to recognize the contributions of the team in research, industry collaboration and teaching. We are around 100 people including academics (chief investigators CIs and associate investigators AIs), research engineers, postdoctoral research fellows, PhD and masters’ students and visitors. We occupy 1000m2 of office and laboratory space at QUT’s Gardens Point campus in downtown Brisbane.
Our heritage goes back to well before 2020. In 2014 we were established as the lead of the Australian Research Council Centre of Excellence for Robotic Vision (ACRV), an investment of nearly $30M and a partnership with other leading Australian and international universities. That Centre finished at the end of 2020 and a summary of its achievements can be found on the Centre’s legacy website.
We have also established a not-for-profit body Robotic Vision Australia which will continue some of the education (Robotic Vision Summer School) and agenda-setting work of the ACRV.
The QUT Centre for Robotics is committed to high-quality research and research training, we publish in top robotics journals and conferences, and develop PhD qualified human capital for leadership in industry and academia. We have a diverse range of industry collaborations spanning applications in agriculture, manufacturing, the natural environment, health and medical, circular economy, space, aerospace, maritime and defence. We train undergraduate engineers in mechatronics and aerospace who we hope will become your future employees. Finally, we engage with the wider public through talks and social media to present a realistic and balanced perspective about what robots can, and (so far) cannot do.
COVID willing, we are planning to hold occasional industry meetups with focus on particular topics in robotics.
Thanks for reading this far. Feel free to send suggestions or feedback about the newsletter to Ilana Bolingford - ilana.bolingford@qut.edu.au
Enjoy the issue.
peter
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Engineers Australia Presentation
CI Jonathan Roberts recently presented to Engineers Australia in their Infrastructure Thought Leader Series: Robotics, Automation and Manufacturing. View the presentation here.
BMW Presentations
CI Michael Milford gave two talks recently. One for public consumption and one to BMW employees. The first talk was a tech overview and careers-focused talk at the Queensland Chapter of the IEEE HKN. The second was an autonomous vehicles-focused talk at the BMW Group Artificial Intelligence and Machine Learning Forum and Technical Seminar Series, capturing aspects of localization and positioning systems including bio-inspired approaches, hosted by Mohsen Kaboli (available internally to BMW Group employees)
Upcoming Talks
AI Daniel Quevedo has two upcoming plenary talks:
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QUT Centre for Robotics Researchers Reach for Space
QUT robotics research is joining the push to take humanity back to the Moon in designing and demonstrating a logistics robot for space application.
Researchers from QUT’s Centre for Robotics will partner with Canadian-based space technology company MDA and Australian Remote Operations for Space and Earth in designing a logistics robot prototype that may be used inside the International Space Station (ISS) or the Lunar Gateway. Read more here.
Lunar Construction Rover Feasibility Project
This project will demonstrate the feasibility of an Australian operated Lunar Construction Rover and Stage 1 Mission scope. The project will investigate and formulate the end-to-end mission concept and align architecture, governance and strategy with NASA’s Artemis mission. The project will develop a business and commercialisation plan to secure further investment.
The project is led by AROSE (Australian Remote Operation in Space and on Earth), a National consortium that QUT Is a member of. Partners in the project are some of the other members of AROSE including: Nova Systems, Woodside, Fleet Space Technologies, Curtin Uni, UNSW.
The project is funded by the Australian Space Agency, in the Moon to Mars Initiative Demonstrator Feasibility Grants.
The project team includes CI Thierry Peynot, Ali Buchberger (Office of Industry Engagement), Garima Samvedi and Dasun Gunasinghe (Research Engineering Facility).
Advanced Terrain Detection - Phase 1
Phase 1 of ATD was completed in August 2021, after 18 months of work in close collaboration with industry partner Rheinmetall Defence Australia (RDA) and collaborator CSIRO (Robotics group). The project is part of a wider program also involving the VRS team (Visual Recognition System) at QUT led by Simon Denman and Clinton Fookes, and RMIT.
The project team included: Guenes Melih Minareci, Bilal Arain, Garima Samvedi, Tim Hojnik (until Feb. 2021), CIs Michael Milford and Thierry Peynot. The project team developed and implemented methods for terrain classification and terrain traversability estimation for RDA’s off-road autonomous ground vehicles. The milestones of the project included reports, software and integration milestones, to demonstrate to RDA executives.
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Verton Technologies Australia
ARM Hub, the Innovative Manufacturing CRC (IMCRC) and QUT (CIs Jonathan Roberts and Matthew Dunbabin) have been working with Verton Technologies Pty Ltd to investigate how robotics can advance the development and manufacturing of its R-Series load management system.
Verton invented an IoT enabled, remote-controlled load-management system that eliminate the need for human held tag lines. Verton’s products not only delivers safer, faster and smarter crane operations, but its AI capabilities create real market advantages by delivering market intelligence, project planning direction, alerts, and product improvement insights. While Verton commenced its collaboration with IMCRC, ARM Hub and QUT experts seeking assistance to robotically manufacture its load orientation products, the company pivoted when the value of the data it could collect became clear.
Today, Verton manufactures high value AI enabled remote control units and offers them as both a product for sale or lease as well as a service. The company has secured international joint ventures and grown from a start-up to a high value exporting Australian SME. Verton now has its sights set on a new big data technology platform set to disrupt the construction industry. Read more here.
Voltin
Voltin, a Brisbane-based SME, has developed a new technology for inspecting high-rise building façades. Through ARM Hub, Voltin were able to access expertise within QUT to guide them through a design to manufacture process. Now beyond prototyping phases, Voltin’s AutoBat2.0 is a full production model. The AutoBAT system automates the recording, evaluation, and reporting of building façade defects, significantly transforming traditional methods of inspection. Their artificial intelligence (AI) enabled engine can be operated safely from the ground to accurately locate and identify defects and anomalies (e.g., peeling paint, water marks, surface cracks, corrosion) and automatically generate inspection reports. ARM Hub has provided industrial design capability; advice about drones, CASA and aerospace science; augmentation of the company’s AI expertise and input to data-as-service business models. In the next stages the ARM Hub will provide Voltin with further industrial design expertise and coordinate specific robotic ‘tooling’ expertise to optimise outcomes.
Since launching in 2020, Voltin has created 5 new jobs and 2 student internship opportunities, anticipating further growth of 8-10 more positions through 2022 and expansion of business into Southeast Asia into 2023.
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ARC ITTC Collaborative Robotics in Advanced Manufacturing
The ARC Industrial Transformation Training Centre for Collaborative Robotics in Advanced Manufacturing is in operation!
The Australian Cobotics Centre officially commenced in August 2021 and is funded for 5 years as part of the Australian Research Council’s Industrial Transformation Research Program (ITRP). The Centre’s is focused on the implementation of collaborative robotics in advanced manufacturing.
Centre Director CI Jonathan Roberts leads a multidisciplinary team of researchers from QUT (where the Centre is headquartered), University of Technology Sydney (UTS), Swinburne University of Technology and TU Dortmund University who will work in collaboration with industry partners (B&R Enclosures, Cook Medical, Weld Australia, InfraBuild, IR4 and ARM Hub.
The Centre aims to improve the collaborative robotics capability within Australian manufacturing by training the next generation of manufacturing leaders, researchers, and technicians with collaborative robotics expertise.
The research programs address both the technological advances and the human and design factors that need to be considered when implementing collaborative robotics. Through this research and its implementation, the Centre will support manufacturers in creating a digitally-capable workforce of the future and a safer, more efficient and globally competitive Australian manufacturing industry.
We are currently recruiting Postdoctoral Research Fellows and PhD students at all our partner universities and all research programs (including Industrial relations, robotics, design, and more).
Visit our website to find out more:
www.AustralianCobotics.org and follow us on Twitter and LinkedIn.
ARC ITTC Joint Biomechanics
CI Michael Milford is an Investigator on the new ARC ITTC for Joint Biomechanics, an Australian Research Council Industrial Transformation Training Centre.
The ITTC brings together leading researchers, end-users and industry partners to train a highly skilled multidisciplinary workforce, capable of creating and applying novel, clinically relevant biomechanical modelling, and simulation platforms, to actively transform the orthopaedic industry. The Centre tackles clinical- and industry-focused challenges in joint biomechanics with the goal to drive surgical practice towards superior personalised patient care. Their vision is to become a leading global joint biomechanical research facility focusing on human shoulder mechanobiology.
Click the image below to view video.
ARC ITRH - Intelligent Robotic Systems for Real-Time Asset Management
CI Niko Sünderhauf is an Investigator on a new ARC Industrial Transformation Research Hub (ITRH) on Intelligent Robotic Systems for Real-Time Asset Management.
This research hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance.
This 5-year Research Hub is funded by the Australian Research Council (ARC) and 11 partners from industry. It is a joint project led the University of Sydney, with QUT and the Australian National University (ANU) in Canberra.
Innovation Connections
CIs Chris Lehnert and Feras Dayoub have been awarded an Innovation Connections Grant worth $100K. The aim of this project is to conduct a feasibility study to identify and assess different technologies and methods for estimating the maturity of watermelons in the field. We look forward to seeing the impact of this project as it progresses.
Max Planck Centre
The ‘Max Planck Centre Queensland for the Materials Science of Extracellular Matrices’ has been awarded to QUT and will be led by D. Prof Dietmar Hutmacher. CI Chris Lehnert will be a member of the soft robotics program of the Centre.
Success Highlights
CI Aaron Mcfadyen was awarded an ARC Discovery Early Career Researcher Award on the topic “Unlocking Urban Airspace for Drone Transport”. Aaron was also awarded an Advance Queensland Industry Research Fellowship for the topic “Drone Management Technology for Improved Aeromedical Response to Pandemics and Natural Disasters.”
CI Michael Milford was awarded an ARC Laureate Fellowship on the topic “Re-Evolving Nature’s Best Positioning Systems for People and Their Machines”.
CI Michael Milford, AI Tobias Fischer and researcher Stephen Hausler were awarded an Amazon Research award to launch a new research program designed to help robot manufacturers develop quality applications at a lower cost leveraging Amazon Web Services (AWS) technology.
New Academic Staff
Professor Will Browne – commenced April 2021
CI Will Browne's expertise is in Artificial Cognitive Systems with over 27 years of experience in Artificial Intelligence and Robotics. The 'Professor and Chair in Manufacturing Robotics' title is through QUT, the ARM Hub and CSIRO who have jointly invested in this position. This is to further University and Industry collaboration in the development of advanced robotics in a wide range of manufacturing, from aquaculture to factory operations to healthcare.
 He is co-PI of the $5 million Science for Technological Innovation, Robotics Spearhead developing the science necessary for human robot collaboration. Will is leading a bid for an Industrial Transformation Research Hub on Digital Manufacturing through the use of artificial intelligence for advancing manufacturing, e.g. effective construction and use of digital twins.
New Administration Team
Ilana Bolingford
Centre Manager – commenced 16 August 2021
 Ilana brings with her extensive experience in the university sector across both QUT and Griffith across HDR student admin, research admin, project management, finance, comms, events, governance, reporting and much, much more. She is also completing her PhD in higher education policy and law and has a Bachelor of Journalism and a Bachelor of Laws from QUT.
Vicki Johnson
Centre Projects and Administration Officer – commenced 6 September 2021
 Vicki has extensive HR and Finance experience and first joined QUT in October 1994 in the Human Resources Department. In 2004 Vicki joined CARRS-Q as their Administration Officer - Finance and has extensive Centre Research knowledge.
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Congratulations to Dr James Mount for being awarded his PhD for his research, "Condition-Invariant Surface-Based Visual Localisation for Multiple Domains and Environments".
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Congratulations to Dr Matt Cooper for being awarded his PhD, “Bayesian System Identification for Nonlinear Dynamical Vehicle Models”.
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CI Peter Corke has been welcomed to the Advisory Board for Brisbane-based mapping and UAV company Emesent.
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PhD student Brendan Tidd was recently part of Team CSIRO Data61 who placed second in the US Government research agency DARPA’s Subterranean Challenge. See more on this here.
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Neuromorphic computing in Artificial Intelligent Systems
Date - 27 July 2021
Presenter - Yulia Sandamirskaya
YouTube
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Decals
Our work area recently got some cool new decals featuring our projects past and present. CI Michael Milford created a video fly-through to showcase the new decals around the lab. Click image to watch the video.
Program videos
QCR now has a set of dynamic feature videos developed by Dahlitz Media | Perfekt Studios. They highlight the work of our research programs: Physical interaction, Perception and localisation, Visual learning and understanding and Decision and control.
Click the links above to view the videos.
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This is a big list but it gives a sense of our research interests. In future editions we will list only publications over the quarter.
Journal articles
Tsai, Dorian; Corke, Peter; Peynot, Thierry; & Dansereau, Donald (2021) Refractive Light-Field Features for Curved Transparent Objects in Structure from Motion. IEEE Robotics and Automation Letters, 6(4).
Bista, Suman Raj; Ward, Belinda; & Corke, Peter (2021) Image-Based Indoor Topological Navigation with Collision Avoidance for Resource-Constrained Mobile Robots. Journal of Intelligent and Robotic Systems, 102(3).
Haviland, Jesse & Corke, Peter (2021) NEO: A novel expeditious optimisation algorithm for reactive motion control of manipulators. IEEE Robotics and Automation Letters, 6(2).
Rahman, Quazi Marufur; Corke, Peter; & Dayoub, Feras (2021) Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends. IEEE Access, 9, pp. 20067-20075.
Rosenberger, Patrick; Cosgun, Akansel; Newbury, Rhys; Kwan, Jun; Ortenzi, Valerio; Corke, Peter, et al. (2021) Object-Independent Human-to-Robot Handovers Using Real Time Robotic Vision. IEEE Robotics and Automation Letters, 6(1).
Xu, Ming; Fischer, Tobias; Sünderhauf, Niko; & Milford, Michael (2021) Probabilistic Appearance-Invariant Topometric Localization with New Place Awareness. IEEE Robotics and Automation Letters, 6(4).
Garg, Sourav & Milford, Michael (2021) SeqNet:Learning Descriptors for Sequence-Based Hierarchical Place Recognition. IEEE Robotics and Automation Letters, 6(3).
Molloy, Timothy L; Fischer, Tobias; Milford, Michael J; & Nair, Girish (2021) Intelligent Reference Curation for Visual Place Recognition via Bayesian Selective Fusion. IEEE Robotics and Automation Letters, 6(2).
Xu, Ming; Sünderhauf, Niko; & Milford, Michael (2021) Probabilistic Visual Place Recognition for Hierarchical Localization. IEEE Robotics and Automation Letters, 6(2).
Mount, James; Xu, Ming; Dawes, Les; & Milford, Michael (2021) Unsupervised selection of optimal operating parameters for visual place recognition algorithms using Gaussian mixture models. IEEE Robotics and Automation Letters, 6(2).
Jacobson, Adam; Zeng, Fan; Smith, David; Boswell, Nigel; Peynot, Thierry; & Milford, Michael (2021) What localizes beneath: A metric multisensor localization and mapping system for autonomous underground mining vehicles. Journal of Field Robotics, 38(1), pp. 5-27.
Laurie, Jordan; Higgins, Niall; Peynot, Thierry; Fawcett, Lisa; & Roberts, Jonathan (2021) An evaluation of a video magnification-based system for respiratory rate monitoring in an acute mental health setting. International Journal of Medical Informatics, 148.
Letheren, Kate; Jetten, Jolanda; Roberts, Jonathan; & Donovan, Jared (2021) Robots should be seen and not heard…sometimes: Anthropomorphism and AI service robot interactions. Psychology and Marketing.
Ali, Shahnewaz; Jonmohamadi, Yaqub; Takeda, Yu; Roberts, Jonathan; Crawford, Ross; & Pandey, Ajay K. (2021) Supervised Scene Illumination Control in Stereo Arthroscopes for Robot Assisted Minimally Invasive Surgery. IEEE Sensors Journal, 21(10).
Mohseni, Soheil; Brent, Alan C; Kelly, Scott; Browne, Will N; & Burmester, Daniel (2021) Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory. International Journal of Electrical Power and Energy Systems, 133.
Siddique, Abubakar; Browne, Will N; & Grimshaw, Gina M (2021) Frames-of-Reference based Learning: Overcoming Perceptual Aliasing in Multi-Step Decision Making Tasks. IEEE Transactions on Evolutionary Computation.
Gao, Guanqiang; Mei, Yi; Xin Bin; Jia, Ya Hui; & Browne, Will N (2021) Automated Coordination Strategy Design Using Genetic Programming for Dynamic Multipoint Dynamic Aggregation. IEEE Transactions on Cybernetics.
Mohseni, Soheil; Brent, Alan C; Kelly, Scott; Browne, Will N; & Burmester, Daniel (2021) Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation. Applied Energy, 287.
Nakata, Masaya & Browne, Will N (2021) Learning Optimality Theory for Accuracy-Based Learning Classifier Systems. IEEE Transactions on Evolutionary Computation, 25(1), pp. 61-74.
Liu, Yi; Browne, Will N; & Xue, Bing (2021) Visualizations for rule-based machine learning. Natural Computing.
Kuhn, Tara; Jayaratne, Rohan; Thai, Phong K; Christensen, Bryce; Liu, Xiaoting; Dunbabin, Matthew; et al. (2021) Air quality during and after the Commonwealth Games 2018 in Australia: Multiple benefits of monitoring. Journal of Aerosol Science, 152.
Jayaratne, Rohan; Thai, Phong; Christensen, Bryce; Liu, Xiaoting; Zing, Isak; Lamont, Riki, et al. (2021) The effect of cold-start emissions on the diurnal variation of carbon monoxide concentration in a city centre. Atmospheric Environment, 245.
In press (Conferences)
Hausler, Stephen; Garg, Sourav; Xu, Ming; Milford, Michael; & Fischer, Tobias (2021) Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 14141-14152. (In Press)
Zhang, Haoyang; Wang, Ying; Dayoub, Feras; & Sünderhauf, Niko (2021) VarifocalNet: An IoU-Aware Dense Object Detector. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021. Institute of Electrical and Electronics Engineers (IEEE), United States of America, pp. 8514-8523. (In Press)
Conference Papers
Garg, Sourav; Fischer, Tobias; & Milford, Michael (2021) Where Is Your Place, Visual Place Recognition? In Zhou, Zhi-Hua (Ed.) Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21). International Joint Conferences on Artificial Intelligence, Montreal, Canada, pp. 4416-4425.
Mandel, Nicolas; Milford, Michael; & Gonzalez, Luis Felipe (2021) Incorporating Hierarchical Information for UAV based Semantic Mapping. In Proceedings of the 2021 IEEE Aerospace Conference. Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 1-11.
Miller, Dimity; Sünderhauf, Niko; Milford, Michael; & Dayoub, Feras (2021) Class Anchor Clustering:A Loss for Distance-based Open Set Recognition. In Proceedings of the 2021 Winter Conference on Applications of Computer Vision (WACV '21). Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 3570-3578.
Tourani, Satyajit; Desai, Dhagash; Parihar, Udit Singh; Garg, Sourav; Sarvadevabhatla, Ravi Kiran; Milford, Michael, et al. (2021) Early bird: Loop closures from opposing viewpoints for perceptually-aliased indoor environments. In Farinella, Giovanni Maria; Radeva, Petia; Braz, Jose; & Bouatouch, Kadi (Eds.) Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Vol. 5. Scitepress, Portugal, pp. 409-416.
Dall'Osto, Dominic; Fischer, Tobias; & Milford, Michael (2021) Fast and Robust Bio-inspired Teach and Repeat Navigation. In IEEE/RSJ International Conference on Intelligent Robots and Systems.
Rahman, Quazi Marufur; Sünderhauf, Niko; & Dayoub, Feras (2021) Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection During Deployment. In Proceedings of the 2021 IEEE Winter Conference on Applications of Computer Vision Workshops (WACVW 2021). Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 152-160.
Moskvyak, Olga; Maire, Frederic; Dayoub, Feras; & Baktashmotlagh, Mahsa (2021) Keypoint-Aligned Embeddings for Image Retrieval and Re-Identification. In Proceedings of the 2021 Winter Conference on Applications of Computer Vision (WACV '21). Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 676-685.
Zhu, Xiaolong; Vanegas, Fernando; Gonzalez, Felipe; & Sanderson, Conrad (2021) A Multi-UAV System for Exploration and Target Finding in Cluttered and GPS-Denied Environments. In Proceedings of the 2021 International Conference on Unmanned Aircraft Systems (ICUAS). Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 721-729.
Galvez-Serna, Julian; Vanegas, Fernando; Gonzalez, Felipe; & Flannery, David (2021) Towards a Probabilistic Based Autonomous UAV Mission Planning for Planetary Exploration. In Proceedings of the 2021 IEEE Aerospace Conference (AERO 2021). Institute of Electrical and Electronics Engineers Inc., United States of America.
Papadopoulos, Ellena & Gonzalez, Luis Felipe (2021) UAV and AI Application for Runway Foreign Object Debris (FOD) Detection. In Proceedings of the 2021 IEEE Aerospace Conference. Institute of Electrical and Electronics Engineers Inc., United States of America.
Shehu, Harisu Abdullahi; Siddique, Abubakar; Browne, Will N; & Eisenbarth, Hedwig (2021) Lateralized Approach for Robustness Against Attacks in Emotion Categorization from Images. In Castillo, Pedro A. & Jiménez Laredo, Juan Luis (Eds.) Applications of Evolutionary Computation:24th International Conference, EvoApplications 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings. Springer, Switzerland, pp. 469-485.
Theses
Kulatunga Mudiyanselage Eranda Bandara Tennakoon
Probe-before-step gait framework for multi-legged robot locomotion over terrains with risk of collapse.
Supervisors – CIs Thierry Peynot and Jonathan Roberts
Douglas Morrison
Robotic grasping in unstructured and dynamic environments.
Principal Supervisor – CI Peter Corke
James Mount
Condition-invariant surface-based visual localisation for multiple domains and environments.
Principal Supervisor – CI Michael Milford
Tim Hojnik
Dynamically configurable centre of rotation wheels.
Supervisors – CIs Matthew Dunbabin and Jonathan Roberts
Matthew Cooper
Bayesian system identification for nonlinear dynamical vehicle models.
Principal Supervisor – CI Jason Ford
Lucian Quach
Application of gestural guided continuum robots in orthopaedic surgery.
Principal Supervisor – CI Jonathan Roberts
Mario Llewellyn Strydom
Robotic manipulation of a human leg for knee arthroscopy.
Principal Supervisor – CI Jonathan Roberts
Chandrama Sarker
Automated detection of flooded areas using machine learning methods.
Supervisors – CIs Luis Alvarez Mejias and Frederic Maire
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