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Status : Active
Research Topic : Intelligence
Socio-Economic Objective : Autonomous and Robotic Systems
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP220100016

    Funder
    Australian Research Council
    Funding Amount
    $475,587.00
    Summary
    Intelligent Robotics for Pharmaceutical Formulation Development. This project aims to transform the labour and time-intensive process of drug formulation development by optimising the process workflow, through collaboration between biochemists and the proposed intelligent and scalable robotic system. This project expects to enable the robot to leverage the expert knowledge of the biochemists while automating rote tasks. The expected outcome of this project is an intelligent robot that can collab .... Intelligent Robotics for Pharmaceutical Formulation Development. This project aims to transform the labour and time-intensive process of drug formulation development by optimising the process workflow, through collaboration between biochemists and the proposed intelligent and scalable robotic system. This project expects to enable the robot to leverage the expert knowledge of the biochemists while automating rote tasks. The expected outcome of this project is an intelligent robot that can collaborate with human coworkers to accelerate drug formulation. This should provide significant benefits by lowering drug costs and the development time of new drugs.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP230101107

    Funder
    Australian Research Council
    Funding Amount
    $470,740.00
    Summary
    Accelerated Finite-time Learning and Control in Cyber-Physical Systems. Efficient learning and control in cyber-physical systems such as smart grids and robotic systems are very important for achieving economic and social benefits. This project aims to establish a breakthrough accelerated finite-time dynamics theory and technology to assist in delivering efficient learning and control. Expected outcomes include new distributed accelerated finite-time dynamics based learning and control algorithm .... Accelerated Finite-time Learning and Control in Cyber-Physical Systems. Efficient learning and control in cyber-physical systems such as smart grids and robotic systems are very important for achieving economic and social benefits. This project aims to establish a breakthrough accelerated finite-time dynamics theory and technology to assist in delivering efficient learning and control. Expected outcomes include new distributed accelerated finite-time dynamics based learning and control algorithms and tools for optimal operations in cyber-physical systems. This should provide significant benefits including a practical technology for industry applications in smart grids and robotic systems, and training of the next generation engineers in this technology for Australia.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE240101245

    Funder
    Australian Research Council
    Funding Amount
    $445,047.00
    Summary
    Automated Modelling Assistance for the Creation of Complex Planning Models. Artificial Intelligence (AI) planning technology is used to control systems like automated factories, robots, or to solve complex optimisation problems. Creating these models is however rather complex and error-prone and requires experts to create them in the first place. This project aims at developing techniques and tools for automated modelling support. They will make the modelling process easier and guarantee desired .... Automated Modelling Assistance for the Creation of Complex Planning Models. Artificial Intelligence (AI) planning technology is used to control systems like automated factories, robots, or to solve complex optimisation problems. Creating these models is however rather complex and error-prone and requires experts to create them in the first place. This project aims at developing techniques and tools for automated modelling support. They will make the modelling process easier and guarantee desired model properties such as the desired system behaviour. The tools will thus contribute towards making the technology more easily accessible to companies that might want to deploy them, while reducing costs for doing so and increasing the quality of these models.
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