Planning mobile robot tasks for autonomous UVC-based COVID-19 sanification of public environments with guaranteed minimum energy distribution

The present essay shows a solution to automize the sanitization process of public environments with UV lamps. Human planning of the procedure may lead to dangerous consequences in case of errors. Therefore, it was chosen to automatically manage the creation of a path that guides the robot through the rooms avoiding obstacles. The project needs the environment map and the selection of areas where sanitization is required. Velocities are defined using optimization techniques to guarantee the distribution of a minimum energy level in all the areas that need sanitization, considering the limited energy autonomy of the robots due to the UV lamps consumption. To demonstrate the validity of the solutions, it was created a simulation in ROS, where a Turtlebot3-Waffle Pi robot performs the sanitization in a simulated environment. The simulation includes several map layers where it is possible to control the state of the lamps and the energy distribution. Once the simulation is over, a control will be performed to check whether the minimum threshold has been reached.