Storytelling has many benefits for people with dementia (PwD), such as improved well-being, confidence and communication. However, there is not much research on robots conducting such activities in dementia care. Thus, the goal of this project was to implement a system that can facilitate a storytelling session between PwD and their family members, keeping them involved through the entire process.

The system uses a Large Language Model (LLM), specifically Gemma 3, to generate responses to user's messages based on carefully written prompts. Other strategies used to facilitate this system are separation of the storytelling phases, turn-taking, story personalisation based on participant's wishes and empathetic responses to participant's responses. To test the system, personas based on PwD and their family members were used.

The results showed that the system successfully facilitates a storytelling session, following the different phases and keeping the participants involved in the process. However, some unexpected behaviour was noticed, for example not switching from one phase to the other on time. These findings demonstrate the potential of LLM-based storytelling robots in dementia care, while also underlining the need for further refinement and testing with real users.