Human recognition for resource-constrained mobile robot applied to Covid-19 Disinfection

The global COVID-19 pandemic has stimulated the use of disinfection robots: in September 2021, following a European Commission's action, 200 disinfection robots were delivered to European Hospitals. UV-C light is a common disinfection method, however, direct exposure to UV-C radiation is harmful and disinfection can be operated only in areas strictly forbidden to human personnel. We believe more advanced safety mechanisms are needed to increase the operational flexibility and safety level. We propose a safety mechanism based on vision and artificial intelligence, optimised for execution on mobile robot platforms. It analyses in real-time four video streaming and disables UV-C lamps when needed. Concerning other detection methods, it has a relatively wider and deeper range, and the capability to operate in a dynamic environment. We present the development of the method with a performance comparison of different implementation solutions, and an on-field evaluation through integration on a mobile disinfection robot.