Find Michael Milford on
PhD (University of Queensland)
I conduct interdisciplinary research at the boundary between robotics, neuroscience and computer vision and am a multi-award winning educational entrepreneur. My research models the neural mechanisms in the brain underlying tasks like navigation and perception to develop new technologies in challenging application domains such as all-weather, anytime positioning for autonomous vehicles. I am also passionate about engaging and educating all sectors of society around new opportunities and impacts from technology including robotics, autonomous vehicles and artificial intelligence. I currently hold the positions of Director of the QUT Centre for Robotics (acting), Professor at the Queensland University of Technology. I have or am leading or co-leading projects totalling more than 48 million dollars in research and industry funding for fellowships and team grants from funding bodies and industry. My papers have won (6) or been finalists (9) for 15 best paper awards including the 2012 ICRA Best Vision paper. My citation h-index is 39, with 8289 citations as of July 2021. I've won multiple awards including being one of only two Australians to ever win a Microsoft Research Faculty Fellowship, the ATSE Batterham Medal (2019) and the Queensland Young Tall Poppy of the Year (2015). I was named the top robotics researcher in Australia by citation impact by The Australian Research Magazine (2019) and was a top 3 finalist for the Australian Museum Eureka Prize for Outstanding Early Career Researcher (2016), the APEC ASPIRE Prize Finalist (2018) and was a finalist in the Reimagine Education Awards Finalist K12 Category. I have dual Australian-US citizenship and have lived and worked in locations including Boston, Edinburgh and London. I have collaborated with organizations including Harvard University, Boston University, Oxford University, MIT, Google Deepmind, Amazon, Ford, Intel, NVIDIA, Caterpillar, the US Air Force Office of Scientific Research and NASA’s Jet Propulsion Laboratory. As a lifelong educational entrepreneur, I have created innovative educational resources for students for 20 years, with customers across 35 countries. My company Math Thrills combines mass market entertainment and STEM education to create math-filled young adult fiction and movie-inspired education. Math Thrills has received funding from Kickstarter, QUTBluebox and the AMP Foundation, honours including being a finalist at the Reimagine Education awards, a TedXQUT talk and a World Science Festival event. We have over 20 titles including The Complete Guide to AI for Kids, the STEM Storybook and Rachel Rocketeer.
Projects (Chief investigator)
- Active, adaptive & predictive robot localization
- Adversity‐ and Adversary‐Robust Adaptive Positioning Systems with Integrity
- Contextually Informed Joint Perception and Localization for Autonomous Vehicles
- Continously updating place descriptors
- Cut Deep: Cutting the Deep network layers for Efficient Representation Learning
- Event-based localisation for ultra-fast systems
- Mining Robotics
- Neuro-Autonomy: Neuroscience-Inspired Perception, Navigation, and Spatial Awareness for Autonomous Robots: AUSMURI project
- Neuromorphic computing
- Neuromorphic sensors and engineering for place recognition
- Out of Line: Sequence Processing and Learning for Localization
- Place-informed Robotics and Autonomous Vehicles
- Re-Evolving Nature’s Best Positioning Systems for People and Their Machines: Australian Research Council Laureate Fellowship 2022-2027
- Reinforcement Learning for Robot Navigation and Interaction
- See 3D: Bridging the Appearance-Geometry gap for 6-DoF, cm-precise visual localization
- Semantic based onboard UAV navigation
- Space Robotics: Scene Understanding for Lunar/Mars Rover
- Terrain Traversability
Projects
- [COMPLETED] ARC Future Fellowship: Superhuman place recognition
- [COMPLETED] Automation-enabling positioning for underground mining
- [COMPLETED] Contextual Hazard Detection
- [COMPLETED] Evaluating the effect of illumination on the performance of visual odometry in underground mining environments
- [COMPLETED] HD maps for automated driving
- [COMPLETED] How automated vehicles will interact with road infrastructure
- [COMPLETED] Mini Autonomous Vehicles
- [COMPLETED] US AFOSR / AOARD: An infinitely scalable learning and recognition network
- AUSMURI: Neuro-Autonomy: Neuroscience-Inspired Perception, Navigation, and Spatial Awareness for Autonomous Robots
- Australian Research Council Industrial Transformation Training Centre for Joint Biomechanics
- Automated Early-Detection of the Invasive Grass African Lovegrass
- Complementarity-Aware Multi-Process Fusion for Long Term Localization
- NVIDIA Applied Research Accelerator Program
- Re-Evolving Nature’s Best Positioning Systems for People and Their Machines
- Reliability in Deep Machine Learning and Uncertainty for Object Detection
- Rheinmetall Defence Australia: Advanced Terrain Detection (ATD)
- Scene Understanding and Semantic SLAM
- Spike-based Visual Place Recognition using Intel’s Loihi
- Visual Place Recognition for Robotics in Extreme Environments
Additional information
I conduct interdisciplinary research at the boundary between robotics, neuroscience and computer vision and am a multi-award winning educational entrepreneur. My research models the neural mechanisms in the brain underlying tasks like navigation and perception to develop new technologies in challenging application domains such as all-weather, anytime positioning for autonomous vehicles. I am also passionate about engaging and educating all sectors of society around new opportunities and impacts from technology including robotics, autonomous vehicles and artificial intelligence. I currently hold the positions of Director of the QUT Centre for Robotics (acting), Professor at the Queensland University of Technology. I have or am leading or co-leading projects totalling more than 48 million dollars in research and industry funding for fellowships and team grants from funding bodies and industry. My papers have won (6) or been finalists (9) for 15 best paper awards including the 2012 ICRA Best Vision paper. My citation h-index is 39, with 8289 citations as of July 2021. I've won multiple awards including being one of only two Australians to ever win a Microsoft Research Faculty Fellowship, the ATSE Batterham Medal (2019) and the Queensland Young Tall Poppy of the Year (2015). I was named the top robotics researcher in Australia by citation impact by The Australian Research Magazine (2019) and was a top 3 finalist for the Australian Museum Eureka Prize for Outstanding Early Career Researcher (2016), the APEC ASPIRE Prize Finalist (2018) and was a finalist in the Reimagine Education Awards Finalist K12 Category. I have dual Australian-US citizenship and have lived and worked in locations including Boston, Edinburgh and London. I have collaborated with organizations including Harvard University, Boston University, Oxford University, MIT, Google Deepmind, Amazon, Ford, Intel, NVIDIA, Caterpillar, the US Air Force Office of Scientific Research and NASA’s Jet Propulsion Laboratory. As a lifelong educational entrepreneur, I have created innovative educational resources for students for 20 years, with customers across 35 countries. My company Math Thrills combines mass market entertainment and STEM education to create math-filled young adult fiction and movie-inspired education. Math Thrills has received funding from Kickstarter, QUTBluebox and the AMP Foundation, honours including being a finalist at the Reimagine Education awards, a TedXQUT talk and a World Science Festival event. We have over 20 titles including The Complete Guide to AI for Kids, the STEM Storybook and Rachel Rocketeer.
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2019
- Details
- 2019 Batterham Medal for Engineering Excellence awarded by the Australian Academy of Technology and Engineering
- Type
- Fellowships
- Reference year
- 2013
- Details
- Microsoft Research Faculty Fellowship, $110,000
- Type
- Membership of Review Panels on Prestigious Grant Applications
- Reference year
- 2016
- Details
- Australian Research Council for Discovery Projects and Discovery Early Career Outstanding Researcher Fellowships
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2013
- Details
- Best Paper Finalist"Towards Condition-Invariant, Top-Down Visual Place Recognition," Michael Milford, Walter Scheirer, Eleonora Vig and David Cox
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2013
- Details
- Ray Jarvis Best Paper Award"Towards Bio-inspired Place Recognition over Multiple Spatial Scales," Zetao Chen, Adam Jacobson, Ugur Murat Erdem, Michael Hasselmo and Michael Milford
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2016
- Details
- Best Paper Finalist Robotics Science and Systems Conference: Milford, M., "Visual Route Recognition with a Handful of Bits", Sydney, Australia, 2012.
- Type
- Membership of Review Panels on Prestigious Grant Applications
- Reference year
- 2013
- Details
- Israeli Ministry of Science & Technology reviewer for Brain Research Infrastructure program grant reviewer
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2012
- Details
- Best Robot Vision Paper Award at the 2012 International Conference on Robotics and Automation
- Type
- Membership of Review Panels on Prestigious Grant Applications
- Reference year
- 2012
- Details
- Canadian Natural Sciences and Engineering Research Council Reviewer for Discovery Grants
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2006
- Details
- Queensland Young Achiever of the Year (Science and Technology)The aims are objectives of the program are to:Acknowledge & highlight the achievements of young Australians.Educate the general public with examples of youth achievement.Encourage & motivate young Australians at all levels in their chosen field of endeavour.Develop a sense of pride in being an Australian.Build self-confidence through rewards for excellence.Provide role models & mentors for our youth by highlighting their achievements and the pursuit of excellence.Develop and encourage leadership and life skills in young Australians.
- Milford, M., (2013). Vision-based place recognition: how low can you go? International Journal of Robotics Research, 32(7), 766–789. https://eprints.qut.edu.au/61609
- Ball, D., Heath, S., Wiles, J., Wyeth, G., Corke, P. & Milford, M. (2013). OpenRatSLAM: an open source brain-based SLAM system. Autonomous Robots, 34(3), 149–176. https://eprints.qut.edu.au/57758
- Maddern, W., Milford, M. & Wyeth, G. (2012). CAT-SLAM: probabilistic localisation and mapping using a continuous appearance-based trajectory. International Journal of Robotics Research, 31(4), 429–451. https://eprints.qut.edu.au/49805
- Maddern, W., Milford, M. & Wyeth, G. (2012). Capping computation time and storage requirements for appearance-based localization with CAT-SLAM. Proceedings of the 2012 IEEE International Conference on Robotics and Automation, 822–827. https://eprints.qut.edu.au/51540
- Milford, M. & Wyeth, G. (2012). SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights. Proceedings of the 2012 IEEE International Conference on Robotics and Automation, 1643–1649. https://eprints.qut.edu.au/51538
- Milford, M., (2012). Visual route recognition with a handful of bits. Robotics: Science and Systems VIII - Proceedings of the 8th Robotics: Science and Systems Conference, 297–304. https://eprints.qut.edu.au/51415
- Milford, M., Wiles, J. & Wyeth, G. (2010). Solving navigational uncertainty using grid cells on robots. PLoS Computational Biology, 6(11), 1–14. https://eprints.qut.edu.au/39472
- Milford, M. & Wyeth, G. (2010). Persistent navigation and mapping using a biologically inspired SLAM system. International Journal of Robotics Research, 29(9), 1131–1153. https://eprints.qut.edu.au/32815
- Milford, M., (2008). Robot navigation from nature: Simultaneous localisation, mapping, and path planning based on hippocampal models. Springer. https://eprints.qut.edu.au/80428
- Milford, M. & Wyeth, G. (2008). Mapping a suburb with a single camera using a biologically inspired SLAM system. IEEE Transactions on Robotics, 24(5), 1038–1053. https://eprints.qut.edu.au/32812
- Title
- ARC Centre of Excellence for Robotic Vision (ACRV)
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- CE140100016
- Start year
- 2014
- Keywords
- Robotic Vision; Robotics; Computer Vision
- Title
- Superhuman Place Recognition with a Unified Model of Human Visual Processing and Rodent Spatial Memory
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- FT140101229
- Start year
- 2015
- Keywords
- Place Recognition; Spatial Memory; Bio-Inspired Robot Navigation
- Title
- Visual Navigation for Sunny Summer Days and Stormy Winter Nights
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DE120100995
- Start year
- 2012
- Keywords
- Vision-Based Navigation; Robot Navigation; Change-Invariant
- Title
- ARC Industrial Transformation Training Centre for Joint Biomechanics
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- IC190100020
- Start year
- 2020
- Keywords
- Global relocalization across changing conditions for metric, keyframe-based visual SLAM systems
PhD, Principal Supervisor
Other supervisors: Professor Niko Suenderhauf
- Direct Visual Hazard Affordance Detection (2019)
- Human Action Recognition and Prediction for Robotics Applications (2019)
- Robust Visual Place Recognition under Simultaneous Variations in Viewpoint and Appearance (2019)
- Bio-Inspired Multi-Sensor Fusion and Calibration for Robot Place Learning and Recognition (2018)
- Learning Real-World Visuo-Motor Policies from Simulation (2018)
- Biologically-inspired Place Recognition with Neural Networks (2016)
- Visual Sequence-Based Place Recognition for Changing Conditions and Varied Viewpoints (2016)
- Continuous Appearance-Based Localisation and Mapping (2014)
- Visual Place Recognition for Persistent Robot Navigation in Changing Environments (2014)