Discovery Early Career Researcher Award - Grant ID: DE210100858
Funder
Australian Research Council
Funding Amount
$344,896.00
Summary
Human-Centred Robot Training. This project aims to address the challenge of effectively enabling novice users to train robots on complex tasks using instructional methods and gamification. With the recent advances of AI research, robots have now better cognitive and functional skills, research in robot training also now allows them to learn interactively from human. Since these robots are expected to provide assistance in different domains including education and healthcare, it is crucial to eff ....Human-Centred Robot Training. This project aims to address the challenge of effectively enabling novice users to train robots on complex tasks using instructional methods and gamification. With the recent advances of AI research, robots have now better cognitive and functional skills, research in robot training also now allows them to learn interactively from human. Since these robots are expected to provide assistance in different domains including education and healthcare, it is crucial to effectively engage human in robot’s instruction. Expected outcomes include new methods for trainers to assess robot learning, and to improve their engagement and feedback. This should provide significant human-robot interaction benefits for accessibility of learning robots.Read moreRead less
Active Segmentation for Cooperative Mobile Robots in Outdoor Environments. The objective of this project is to develop a principled understanding of how to improve the segmentation of three-dimensional range data in a cooperative manner by judiciously choosing future sensor viewpoints of a team of mobile robots. The viewpoint of the robot affects both the density of three-dimensional data points and the areas that are unobservable due to occlusions. Project outcomes will open up a whole new appr ....Active Segmentation for Cooperative Mobile Robots in Outdoor Environments. The objective of this project is to develop a principled understanding of how to improve the segmentation of three-dimensional range data in a cooperative manner by judiciously choosing future sensor viewpoints of a team of mobile robots. The viewpoint of the robot affects both the density of three-dimensional data points and the areas that are unobservable due to occlusions. Project outcomes will open up a whole new approach to the process of autonomously gathering information about objects in outdoor environments, will synergise with existing classification and motion planning methods, and will support Australia's continued role as a leader in field robotics research.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH210100030
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The ex ....ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The expected outcomes are robots with the ability to autonomously collect data for integration into a digital twin that provides a real-time representation of the true state of a physical asset. The benefits include both improved asset management and establishing Australia as a leading manufacturer of advanced robotic systems.Read moreRead less
Supporting Responses To Commonwealth Science Council Priorities - Grant ID: CS170100007
Funder
Australian Research Council
Funding Amount
$208,595.00
Summary
The Internet of Things: maximising the benefit of deployment in Australia. This project aims to examine the opportunities, risks and consequences of the Internet of Things (IoT) and establish ways to foster technological leadership while ensuring responsible deployment. This project explores the immense potential that the Internet of Things offers for Australia – the productivity and safety of our industries, the efficiency and impact of services, and our ability to contribute skilled jobs to th ....The Internet of Things: maximising the benefit of deployment in Australia. This project aims to examine the opportunities, risks and consequences of the Internet of Things (IoT) and establish ways to foster technological leadership while ensuring responsible deployment. This project explores the immense potential that the Internet of Things offers for Australia – the productivity and safety of our industries, the efficiency and impact of services, and our ability to contribute skilled jobs to the growing global digital economy. These analyses will clarify the economic, social and cultural perspectives of deployment and establish a set of key findings to guide policy making over the next decade.Read moreRead less
Advanced three-dimensional Computer Vision Algorithms for 'Find and Grasp' Future Robots. This project addresses crucial limitations of existing vision systems for the robot grasping of irregular objects in messy living environments. This project aims to undertake fundamental research into novel three-dimensional vision algorithms, exploiting multiple modalities (two-dimensional+three-dimensional+video) for scene labelling, object classification, scene segmentation and grasp synthesis to enable ....Advanced three-dimensional Computer Vision Algorithms for 'Find and Grasp' Future Robots. This project addresses crucial limitations of existing vision systems for the robot grasping of irregular objects in messy living environments. This project aims to undertake fundamental research into novel three-dimensional vision algorithms, exploiting multiple modalities (two-dimensional+three-dimensional+video) for scene labelling, object classification, scene segmentation and grasp synthesis to enable future robots to operate in unstructured environments with highly occluded and cluttered objects. It is expected to significantly advance research and to have broad applications, including home robotics to improve the quality of life of elders and people with special needs. These algorithms may also be used in security (explosive manipulation) and agriculture (field crop harvesting).Read moreRead less
Modelling and simulation of self-organised behaviour in biological and bio-inspired systems. Understanding self-organised systems is fundamental in biology and bio-inspired engineering. The project develops sophisticated mathematical modelling techniques and high performance simulation methods for such systems. This will increase our capacity to explain complex biological behaviour and to produce reliable bio-inspired engineering solutions