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Research Topic : Robotics
Australian State/Territory : VIC
Socio-Economic Objective : Autonomous and Robotic Systems
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Control engineering mechatronics and robotics (2)
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP220100417

    Funder
    Australian Research Council
    Funding Amount
    $285,684.00
    Summary
    Muscle-based Signals for Responsive Physically-Assistive Robotics. This project aims to develop a physically assistive robot for industrial use that interprets signals from the human user’s muscles during a physical activity and responds with appropriate assistance. This is significant because the robot must accommodate the complexity of movement required in industrial settings and adapt to variabilities in muscle activation signals among users that also change in time. The expected research out .... Muscle-based Signals for Responsive Physically-Assistive Robotics. This project aims to develop a physically assistive robot for industrial use that interprets signals from the human user’s muscles during a physical activity and responds with appropriate assistance. This is significant because the robot must accommodate the complexity of movement required in industrial settings and adapt to variabilities in muscle activation signals among users that also change in time. The expected research outcome is an intuitive, assistive robot worn by the human workforce that enhances their productivity and longevity, improves working conditions, lowers production costs, and increases workforce resilience. The robot’s capabilities will be demonstrated in this project through the challenging activity of sheep shearing.
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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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