UVC Dose Mapping by Mobile Robots

Abstract

Hospital-acquired infections are a persistent and increasing problem and their prevention involves disinfecting areas and surfaces. The necessity for effective disinfection methods has highly increased in consequence of the Covid-19 pandemic. An effective method is using UVC exposure because UVC radiation is absorbed by nucleic acids and, therefore, is able to inactivate microorganisms. This method also brings many advantages when compared with traditional disinfection methods. UVC disinfection can be performed by fixed equipments that have to be moved from place to place to disinfect an entire area, or by an autonomous mobile equipment that requires minimal human intervention to completely disinfect an environment. This dissertation is focused on mobile robots that disinfect an environment using UVC radiation. These mobile robots are able to move autonomously while mapping the surrounding environment and simultaneously disinfect it. The robots keep track of the dose applied to each area of the environment in order to build a dose map and differentiate areas that are completely disinfected from those that are not. This solution has the advantage of the robot performing UVC disinfection without needing to stop in each area nor having previous knowledge of the environment. The validation of this solution was performed using rviz, a Robot Operating System (ROS) tool, and the LiDAR Camera L515. The camera was used to capture the necessary information for creating the map of the environment and rviz was used to visualize the dose map.