PhD Project

Long-term behavior learning for robot-assisted recovery after critical injury.

Socially Assistive Robots (SARs) have demonstrated strong potential in rehabilitative scenarios due to their positive effect on user engagement and suitability for tasks traditionally undertaken by expert therapists. For SARs supporting recovery from upper-limb injuries, user personalization is key to sustaining engagement over the long term. This project attempts to utilize participatory design with expert physiotherapists to develop and train, through interactive reinforcement learning, an SAR companion which adapts its behaviour in real time to the needs and preferences of a person recovering from upper-limb injury.

Human-Robot Interaction Personalisation Reinforcement Learning Python ROS Assistive Robotics Social Robots Paticipatory Design Intelligent Interactive Systems