Improving UV Disinfection of Objects by a Robot Using Human Feedback

Abstract

Ultraviolet-C (UV-C) robot irradiation is a promising approach for disinfecting surfaces contaminated by pathogens in healthcare settings. However, limitations exist with current UV disinfection robots, including coverage for complex surface geometries. This research presents a system for human-guided robotic UV disinfection that uses empirical sensor measurements rather than relying on high-accurate models for UV map coverage. Human guidance is integrated into the methodology to enhance disinfection, aiding in addressing complex shaped objects and topologies. Further, a validation test confirmed that our estimation approach reliably underestimates the UV exposure, which is beneficial for ensuring thorough disinfection. Initial user studies demonstrated that while autonomous disinfection was effective for simple objects like tabletops, human-guided disinfection, especially with feedback, improved coverage and speed for complex shapes like mugs. Combining human intuition with autonomy shows potential for enhancing robotic disinfection effectiveness.