As the global population ages, many older adults face challenges related to cognitive decline, social isolation, and reduced independence. Social robots have shown promise in supporting aged care by reducing apathy and loneliness, but for these technologies to be truly effective, they must interact in ways that feel natural, empathetic, and engaging.

This PhD project, in collaboration with Andromeda Robotics, focuses on developing algorithms that improve Abi’s (Andromeda’s companion robot) abilities to communicate and engage in sustained and meaningful interactions with elderly residents. Specifically, the project will design and evaluate:

1. Non-verbal gesture generation – creating expressive movements that convey the robot’s affective and cognitive states.
2. User adaptation – developing learning-based algorithms that respond to changes in user engagement during interaction.
3. System adaptation – ensuring behaviours remain robust and natural despite the robot’s hardware and software limitations.

The research combines lab-based studies to validate that Abi’s movements are clear and easy to understand and in-situ evaluations in aged care settings to see how these improvements affect residents’ sense of connection, empathy, and warmth toward the robot. Ultimately, this work aims to demonstrate how sustained engagement with social robots can foster positive social connections and support cognitive health among older adults.