As robots become more prevalent in our daily lives, there is an increasing need for them to be able to interact with humans in a social and intuitive manner. Even though Robot and AI technologies have rapidly developed in recent years, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge is to determine how to design robots that can perceive the user’s needs, feelings and intentions, and adapt to users over a broad range of cognitive abilities. In particular, how the robot could react to human partners showing different behaviours, and how human-robot interactive behaviours might potentially reveal novel aspects of human personality and health.
In this project, the student will develop robot control and machine learning methods on the UR3e robotic arm testbed (with haptic sensors) to autonomously control a robot to physically interact with human collaborators (clap hands, jointly move an object, etc.) showing different behaviours. The student will use machine learning methods to extract behaviour patterns and then design robot control methods (PID and continuous learning methods) to control the robotic arm to move with specific behaviour patterns. Furthermore, we will study how to use robot and joint human-robot behaviours to elicit and identify aspects of human personality and health.
The project’s impact will be broad, affecting health, neuroscience, social robotics and fundamental robot research. The output of the project can be published in various journals and conferences, such as IEEE International Conference on Robotics and Automation (ICRA), IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), ACM/IEEE International Conference on Human-Robot Interaction, Science Robotics, Journal of Neural Engineering, and Frontiers in psychology, etc.
Eligibility
Applicants must have or expect to obtain the equivalent of a 1st or 2:1 degree in any subject relevant to the CDT including, but not limited to, computing science, psychology, linguistics, mathematics, sociology, engineering, physics, etc.
Applicants will be asked to provide two references as part of their application.
Funding Notes
Funding is available to cover the annual tuition fees for UK home applicants, as well as an annual stipend at the standard UKRI rate (currently £17,668 for 2022/23). To be classed as a home applicant, candidates must meet the following criteria:
- Be a UK National (meeting residency requirements), or
- Have settled status, or
- Have pre-settled status (meeting residency requirements), or
- Have indefinite leave to remain or enter.
As per UKRI funding guidelines, up to 30% of studentships may be awarded to international applicants who do not meet the UK home status requirements. Funding for successful international students will match that of home students and no international top-up fees will be payable.
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