Picture this! An A-Team of flying robots able to autonomously communicate and navigate, swiftly reaching GPS black spots in time-critical search and rescue missions including inside collapsed buildings or underground mines.
This vision is one step closer to reality thanks to a Federal Government funding injection to advance research led by Australian Centre for Robotic Vision Associate Investigator Felipe Gonzalez. The project – ‘When every second counts: multi-drone navigation in GPS-denied environments’ – also focuses on mapping natural environments, including under tree canopies, to help manage and safeguard diverse ecologies.
It is one of five research collaborations involving Centre researchers to this week make the cut in a line-up of 660 new Australian Research Council (ARC) Discovery Projects, collectively worth $285 million.
Awarded close to $2 million, the five projects involving researchers from across the Centre’s four university nodes (QUT, Monash University, The Australian National University and University of Adelaide) are:
When every second counts: Multi-drone navigation in GPS-denied environments ($360,000 / QUT)
Associate Professor Felipe Gonzalez; Associate Professor Jonghyuk Kim; Professor Sven Koenig; Professor Kevin Gaston
The aim of this research is to develop a framework for multiple Unmanned Aerial Vehicles (UAV), that balances information sharing, exploration, localization, mapping, and other planning objectives thus allowing a team of UAVs to navigate in complex environments in time critical situations. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining Simultaneous Localization and Mapping (SLAM) algorithms with Partially Observable Markov Decision Processes (POMDP) and Deep Reinforcement learning. This should provide significant benefits, such as more responsive search and rescue inside collapsed buildings or underground mines, as well as fast target detection and mapping under the tree canopy.
Active Visual Navigation in an Unexplored Environment ($450,000 / University of Adelaide)
Professor Ian Reid; Dr Seyed Hamid Rezatofighi
This project will develop a new method for robotic navigation in which goals can be specified at a much higher level of abstraction than has previously been possible. This will be achieved using deep learning to make informed predictions about a scene layout, and navigating as an active observer in which the predictions informs actions. The outcome will be robotic agents capable of effective and efficient navigation and operation in previously unseen environments, and the ability to control such agents with more human-like instructions. Such capabilities are desirable, and in some cases essential, for autonomous robots in a variety of important application areas including automated warehousing and high-level control of autonomous vehicles.
Deep Learning that Scales ($390,000 / University of Adelaide)
Professor Chunhua Shen
Deep learning has dramatically improved the accuracy of a breathtaking variety of tasks in AI such as image understanding and natural language processing. This project addresses fundamental bottlenecks when attempting to develop deep learning applications at scale. First, this project proposes efficient neural architecture search that is orders of magnitude faster than previously reported, abstracting away the most complex part of deep learning. Second, we will design very efficient binary networks, enabling large-scale deployment of deep learning to mobile devices. Thus this project will overcome two primary limitations of deep learning generally, however, and will greatly increase its already impressive domain of practical application.
3D Vision Geometric Optimisation in Deep Learning ($390,000 / The Australian National University)
Professor Richard Hartley; Dr Miaomiao Liu
This project aims to develop a methodology for integrating the algorithms of 3D Vision Geometry and Optimization into the framework of Machine Learning and demonstrate the wide applicability of the new methods on a variety of challenging fundamental problems in Computer Vision. These include 3D geometric scene understanding, and estimation and prediction of human 2D/3D pose and activity. Applications of this technology are to be found in Intelligent Transportation, Environment Monitoring, and Augmented Reality, applicable in smart-city planning and medical applications such as computer-enhanced surgery. The goal is to build Australia’s competitive advantage in the forefront of ICT research and technology innovation.
Advancing Human–robot Interaction with Augmented Reality ($360,000 / Monash University)
Professor Elizabeth Croft; Professor Tom Drummond; Professor Hendrik F. Van der Loos
This research aims to advance emerging human-robot interaction (HRI) methods, creating novel and innovative, human-in-the-loop communication, collaboration, and teaching methods. The project expects to support the creation of new applications for the growing wave of assistive robotic platforms emerging in the market and de-risk the integration of collaborative robotics into industrial production. Expected outcomes include methods and tools developed to allow smart leveraging of the different capacities of humans and robots. This should provide significant benefits allowing manufacturers to capitalize on the high skill level of Australian workers and bring more complex high-value manufactured products to market.
Shelley Thomas, Communications Specialist
Australian Centre for Robotic Vision
P: +61 7 3138 4265 | M: +61 416 377 444 | E: email@example.com
About The Australian Centre for Robotic Vision
The Australian Centre for Robotic Vision is an ARC Centre of Excellence, funded for $25.6 million over seven years to form the largest collaborative group of its kind generating internationally impactful science and new technologies that will transform important Australian industries and provide solutions to some of the hard challenges facing Australia and the globe. Formed in 2014, the Australian Centre for Robotic Vision is the world’s first research centre specialising in robotic vision. They are a group of researchers on a mission to develop new robotic vision technologies to expand the capabilities of robots. Their work will give robots the ability to see and understand for the sustainable well-being of people and the environments we live in. The Australian Centre for Robotic Vision has assembled an interdisciplinary research team from four leading Australian research universities: QUT, The University of Adelaide (UoA), The Australian National University (ANU), and Monash University as well as CSIRO’s Data61 and overseas universities and research organisations including the French national research institute for digital sciences (INRIA), Georgia Institute of Technology, Imperial College London, the Swiss Federal Institute of Technology Zurich (ETH Zurich), University of Toronto, and the University of Oxford.
Australian Centre for Robotic Vision
2 George Street Brisbane, 4001
+61 7 3138 7549