Human models for accelerated robot learning and human-robot interaction. This project aims to develop novel approaches to teach robots to proficiently interact with humans in a safe and low-cost manner. To achieve this aim, this project will develop novel models from which various human behaviours can be generated and used to train human-robot interaction policies in simulation. Expected outcomes of this project include new computational models of human behaviour built using cognitive science th ....Human models for accelerated robot learning and human-robot interaction. This project aims to develop novel approaches to teach robots to proficiently interact with humans in a safe and low-cost manner. To achieve this aim, this project will develop novel models from which various human behaviours can be generated and used to train human-robot interaction policies in simulation. Expected outcomes of this project include new computational models of human behaviour built using cognitive science theories and limited data and new training schemes for robot learning in simulation. By training robots in simulation with accurate human models, this research will enable fast and safe robot training to support the deployment and adoption of robots in human contexts such as healthcare facilities, homes, and workplaces.Read moreRead less
Visual methods for advanced automation of underwater manipulation. This project will increase the autonomy of underwater robotic systems engaged in intervention and inspection tasks. Such activities are essential for the operation of subsea robotic systems used in offshore industries, scientific exploration and defence. Our approach will improve perception and situational awareness through the principled fusion of multiple navigation and camera sensors. We will use this improved scene understand ....Visual methods for advanced automation of underwater manipulation. This project will increase the autonomy of underwater robotic systems engaged in intervention and inspection tasks. Such activities are essential for the operation of subsea robotic systems used in offshore industries, scientific exploration and defence. Our approach will improve perception and situational awareness through the principled fusion of multiple navigation and camera sensors. We will use this improved scene understanding to effectively plan the motion of vehicles and manipulators through larger and more complex workspaces, enabling semi-supervised and autonomous task execution. Our project will demonstrate these capabilities in real-world deployments relevant to industry and marine science.Read moreRead less
Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques ....Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100960
Funder
Australian Research Council
Funding Amount
$420,198.00
Summary
Reverse Design of Tuneable 4D Printed Materials for Soft Robotics. This project aims to facilitate the design and manufacture of specialised objects that can change their shape over time. These types of objects are made from ‘tuneable metamaterials’, which can be made by 4D printing: 3D printing with an added dimension of time. These materials are becoming indispensable in many fields- including non-metallic soft robots used in medicine or the exploration of harsh environments like space- but ar ....Reverse Design of Tuneable 4D Printed Materials for Soft Robotics. This project aims to facilitate the design and manufacture of specialised objects that can change their shape over time. These types of objects are made from ‘tuneable metamaterials’, which can be made by 4D printing: 3D printing with an added dimension of time. These materials are becoming indispensable in many fields- including non-metallic soft robots used in medicine or the exploration of harsh environments like space- but are currently onerous to make. This project will develop a revolutionary new method for a user to work backward from defining the desired qualities to the manufacture of the object that satisfies their needs. It will also create a library that will allow users to quickly select a material that will be appropriate.Read moreRead less
Robots as a Social Group: Implications for Human-Robot Interaction. This Project aims to identify psychological factors that can limit the acceptance of robots in the home and workplace. As robots become more pervasive in everyday life, they are also likely to elicit fear, rejection, and even damage. The significance of the Project lies in its social neuroscientific approach to promoting better human-robot interaction by considering robots as a social group. Expect outcomes include theory develo ....Robots as a Social Group: Implications for Human-Robot Interaction. This Project aims to identify psychological factors that can limit the acceptance of robots in the home and workplace. As robots become more pervasive in everyday life, they are also likely to elicit fear, rejection, and even damage. The significance of the Project lies in its social neuroscientific approach to promoting better human-robot interaction by considering robots as a social group. Expect outcomes include theory development about human and robot intergroup acceptance, enhanced institutional and international collaborations, and much needed psychological knowledge for robot designers. Benefits include a detailed understanding of how to increase the acceptance of robots in a wide variety of fields.Read moreRead less
Home helper robots: Understanding our future lives with human-like AI. This fellowship aims to understand and plan for the social effects of embedding ‘cute’ home helper robots into people’s everyday lives. The project is expected to generate new knowledge and resources to understand and respond to the emerging opportunities and risks associated with home helper robots, including their ability to support household tasks, and to provide child and aged care and companionship. Expected outcomes inc ....Home helper robots: Understanding our future lives with human-like AI. This fellowship aims to understand and plan for the social effects of embedding ‘cute’ home helper robots into people’s everyday lives. The project is expected to generate new knowledge and resources to understand and respond to the emerging opportunities and risks associated with home helper robots, including their ability to support household tasks, and to provide child and aged care and companionship. Expected outcomes include an improved understanding of anthropomorphised robots in everyday life and innovation in home helper robot theory and imaginaries. This should provide benefits such as informing robot design and policy to improve social outcomes, consumer protections and human-robot relationships.Read moreRead less