Visual Simultaneous Localisation and Mapping in Deformable Environments. This project aims to investigate the problem of building a three-dimensional map of a deformable environment in real-time using images and at the same time localising the camera within the map. This project expects to generate new knowledge in the area of simultaneous localisation and mapping in deformable environments using visual sensors. Expected outcomes include in-depth understanding of the fundamental sensing requirem ....Visual Simultaneous Localisation and Mapping in Deformable Environments. This project aims to investigate the problem of building a three-dimensional map of a deformable environment in real-time using images and at the same time localising the camera within the map. This project expects to generate new knowledge in the area of simultaneous localisation and mapping in deformable environments using visual sensors. Expected outcomes include in-depth understanding of the fundamental sensing requirements for the problem to be solvable, the achievable accuracy, and efficient algorithms for achieving accurate three-dimensional reconstruction of deformable environments. The research outcomes from this project offer significant benefits to diverse areas such as minimally invasive robotic surgery.Read moreRead less
Robotic Perception with Unconventional Sensors . Autonomy in robotic systems currently relies on conventional sensors such as lasers and cameras. Alternative sensing modalities as in the case of active electromagnetic sensors are commonly used to detect flaws, cracks and assess infrastructure’s integrity, however, fundamental research questions preclude their use for robotic perception. This project will develop the theory and algorithms to enable perception tasks such as localisation, mapping a ....Robotic Perception with Unconventional Sensors . Autonomy in robotic systems currently relies on conventional sensors such as lasers and cameras. Alternative sensing modalities as in the case of active electromagnetic sensors are commonly used to detect flaws, cracks and assess infrastructure’s integrity, however, fundamental research questions preclude their use for robotic perception. This project will develop the theory and algorithms to enable perception tasks such as localisation, mapping and recognition with unconventional sensors. The outcomes of this research have the potential to improve the effectiveness of critical civil infrastructure maintenance technology through accurate and reliable inspections, and the reduced need for human intervention.Read moreRead less
Development of globally optimal solutions to simultaneous localisation and mapping for robot navigation. Building robots that can operate on their own is one of the potentially transformational technologies of this century. This project will develop algorithms that are well understood and robust to allow the deployment of robots in environments populated with people and in search and rescue operations where global positioning system is not available.
Discovery Early Career Researcher Award - Grant ID: DE130100885
Funder
Australian Research Council
Funding Amount
$374,723.00
Summary
Aerial robots contacting objects in dynamic environments. This project will allow small unmanned aerial vehicles to touch objects to perform tasks and to fly confidently in complex and cluttered environments where contact with surroundings is inevitable. This will enable robots to perform critical tasks such as servicing power lines, bridges and other elevated infrastructure.
Supervised autonomy for AUVs using limited bandwidth communication channels. This project aims to improve the feedback link between robotic platforms and an operator, to increase the effectiveness of underwater survey operations. During surveys, some level of adaptation is required to allow underwater robots to respond to the data they are collecting. It is often difficult to reliably program an autonomous system to identify salient data, particularly when the mission involves searching for part ....Supervised autonomy for AUVs using limited bandwidth communication channels. This project aims to improve the feedback link between robotic platforms and an operator, to increase the effectiveness of underwater survey operations. During surveys, some level of adaptation is required to allow underwater robots to respond to the data they are collecting. It is often difficult to reliably program an autonomous system to identify salient data, particularly when the mission involves searching for particular features whose sensor signatures may be difficult to determine a priori. In contrast, humans are generally good at quickly identifying important data or determining when a mission is not achieving its goals. The project aims to develop novel acoustic communication schemes that will allow communication between the human operator and the underwater robot, exploiting developments in machine learning, network and communication theory.Read moreRead less
Robotics for zero-tillage agriculture. This project will develop small agricultural robots to increase broad-acre crop production and reduce environmental impact. These robots will have advanced navigation capability, will cooperate to cover large areas and resupply themselves, while causing less soil damage and applying herbicide more intelligently.
Unifying Foundations for Intelligent Agents. This project aims to drive forward the development of rigorous foundations for intelligent agents. The agent framework, the expected utility principle, sequential decision theory, and the information-theoretic foundations of inductive reasoning and machine learning have already brought significant order into the previously heterogeneous scattered field of artificial intelligence. This project aims to investigate an information-theoretic approach towar ....Unifying Foundations for Intelligent Agents. This project aims to drive forward the development of rigorous foundations for intelligent agents. The agent framework, the expected utility principle, sequential decision theory, and the information-theoretic foundations of inductive reasoning and machine learning have already brought significant order into the previously heterogeneous scattered field of artificial intelligence. This project aims to investigate an information-theoretic approach towards a unifying foundation for intelligent agents, which has recently spawned impressive applications. The theory is expected to provide a gold standard and valuable guidance for researchers working on smart software.Read moreRead less
Feature reinforcement learning. Agent applications include speech recognition systems, vision systems, search engines, auto-pilots, spam filters, and robots. The research outputs from this project will enable agents to adapt to their environment and automatically, during deployment, acquire much of the knowledge that is currently required to be built in by agent designers.
On-line planning for constrained autonomous agents in an uncertain world. This project aims to develop admissible heuristics for constrained stochastic planning problems and integrate them into state-of-the-art on-line algorithms. Artificial Intelligence (AI) systems, such as self-driving cars or energy management systems, make intelligent decisions to act near-optimally in uncertain environments, leading to savings, for example in energy use. But we also want assurances that AI systems will obe ....On-line planning for constrained autonomous agents in an uncertain world. This project aims to develop admissible heuristics for constrained stochastic planning problems and integrate them into state-of-the-art on-line algorithms. Artificial Intelligence (AI) systems, such as self-driving cars or energy management systems, make intelligent decisions to act near-optimally in uncertain environments, leading to savings, for example in energy use. But we also want assurances that AI systems will obey safety constraints. Solving constrained stochastic planning problems is key to building AI that is both robust and safe. This project will explore ways to account for uncertainty and constraints in heuristic estimation.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