Research on Graph-Based SLAM for UVC Disinfection Robot

Abstract

With the emergence of the COVID-19 pandemic, more and more non-contact mobile disinfection robots have appeared in the medical field, which have made great contributions to the fight against the epidemic. Aiming at the problems of single disinfection method, single application scenario, low degree of intelligence and lack of autonomous mobile disinfection in existing disinfection robots, this paper proposes and designs a disinfection and epidemic prevention intelligent robot called Aimi-Robot UVC, which is based on graph-optimized slam algorithm to complete the localization and map creation functions of the robot in the unknown environment. After testing in the isolated single ward of the hospital, the realtime localization accuracy reaches 0.04m, which provides high-precision and high-reliability localization for the disinfection robot in the hospital scene and has great practical significance for the application of intelligent disinfection robots in epidemic prevention and control.