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‘I need help but my robot can’t get down the stairs’: a healthcare architecture focused study

While robots and AI assistants continue to improve at a rapid pace, they have been unable to achieve widespread usage in social housing.

A contributing aspect that is often overlooked is that of the built environment and how robots behave in these different spaces. We are focusing on factors affecting the cohabitation of robots and people with frailty. We have investigated the real home environments of those living with frailty. This will inform target areas that need improving and further scrutiny to future-proof living environments for both humans and their robotic companions.

Methodology

We have presented a methodology for creating realistic, scalable and reproducible built environments to simulate robot behaviour. This approach enables the prediction of robot-human cohabitation suitability and provides insights into designing spaces that accommodate both. It allows for detailed observation without the time, financial and logistical constraints of physical robot deployment. However, the methodology has some limitations. The CAD-based models do not fully capture environmental textures, such as carpets or reflective surfaces, which may affect robot sensors.

Testing longitudinally in real environments is now paramount as we have uncovered some limitations in simulations and lab-based experimentation. Furthermore, our process for scanning and scaling will be used to approach more social housing and government representatives to suggest future-proof initiatives for new builds and refurbishments for housing.

Project lead

Picture of Fernando Loizides

Dr Fernando Loizides

Reader (Associate Professor)- Director of the Data Science Academy

Telephone
+44 29208 79160
Email
LoizidesF@cardiff.ac.uk

Funded by

EPSRC EMERGENCE

Project partner

University College London, Hobbs Rehabilitation.