Cooperative control of networked systems with constraints. This project aims to address the challenge of networked systems in deploying teams of robotic agents. Control of the networked system is extremely difficult due to real world constraints imposed on each agent. This project will focus on motion constraints, equipment/capability constraints, and spatial constraints. In addition to theoretical advances, the wider scientific community will benefit directly, because the control algorithms dev ....Cooperative control of networked systems with constraints. This project aims to address the challenge of networked systems in deploying teams of robotic agents. Control of the networked system is extremely difficult due to real world constraints imposed on each agent. This project will focus on motion constraints, equipment/capability constraints, and spatial constraints. In addition to theoretical advances, the wider scientific community will benefit directly, because the control algorithms developed are expected to allow straightforward deployment of robotic teams. There are myriad applications for cooperative robotic agents, ranging from surveillance, to environmental monitoring using underwater and aerial drone formations – with an array of benefits and impacts including economic, commercial and societal. The results are intended to ensure and cement Australia’s front-line position in the current technological revolution known as “Industry 4.0”.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102388
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
From Bayesian filtering to smoothing and prediction for multiple object systems. This project will develop new and improved algorithms for tracking multiple targets, such as tanks, submarines or planes, using the state of the art in mathematical and computational design. These will enable more efficient and accurate technologies for defence related applications including intelligence, surveillance and reconnaissance.
Parameter estimation for multi-object systems. Parameter estimation in multi-object system is essential to the application of multi-object filtering to a wider range of practical problems with social and commercial benefits. This project develops the necessary parameter estimation techniques for complete 'plug-and-play' multi-object filtering solutions that facilitates widespread applications.
Control and Optimization of Distributed Multiagent Formations. The project aims to develop a conceptual framework and algorithms for handling multi-vehicle formation control. Formations of unmanned airborne vehicles are currently used by defence forces and swarms of micro-vehicles are beginning to find increasing use in defence and for civilian emergency response, largely for surveillance purposes. Vehicles must cooperate to achieve a global formation objective, while respecting constraints on s ....Control and Optimization of Distributed Multiagent Formations. The project aims to develop a conceptual framework and algorithms for handling multi-vehicle formation control. Formations of unmanned airborne vehicles are currently used by defence forces and swarms of micro-vehicles are beginning to find increasing use in defence and for civilian emergency response, largely for surveillance purposes. Vehicles must cooperate to achieve a global formation objective, while respecting constraints on sensors, energy, and general mechanical limitations. The project aims to resolve the challenges of deciding what a single vehicle should observe, what and to where it should communicate, and how it should move in relation to what it sees. The conceptual framework developed may also be relevant in guiding future defence acquisitions and civilian applications.Read moreRead less
A stochastic geometric framework for Bayesian sensor array processing. This project develops a mathematical framework, and a new generation of techniques, for sensor array processing to address real-world problems with uncertainty in array parameters and number of signals. The outcomes will enhance the capability of sensors in many application areas including, radar, sonar, astronomy and wireless communications.