## 1 Introduction  
The health sector is currently under enormous pressure, especially to cope with staff shortages and the loss of capacity due to staff infections with the coronavirus and various other diseases. Health facilities are generally among the most at-risk areas of infection with various viruses or infections [1]. Therefore, maintaining a clean environment in these facilities is crucial for reducing future pressure on medical capacity. However, ensuring proper disinfection to prevent transfers places increased demands on the staff who must carry out these cleaning procedures [2]. Some disinfection activities of the staff cannot be replaced, but some can be automated and transferred to the disinfection automated guided vehicle (AGV) [3]. An AGV is a device that can move in an area autonomously and, during its movement, disinfect the area through disinfection equipment. Presently, we can see an increase in interest in such technologies globally [4]. This is also thanks to the development of security systems, which are most important in areas with a high movement of people and prevent collisions with unexpected obstacles [5]. Such obstacles are all objects and people in the area for whom the control system has no information [6]. The algorithms of the AGV control unit are designed to be able to perform the specified disinfection task safely and reliably. When a new task is received, it is first verified that the AGV system can perform the task. The estimated electricity consumption needed to perform the task is then calculated, which consists of the sum of the routes of the movements necessary to complete the task and the consumption needed to return the AGV to its starting position [7, 8]. Consequently, this estimated consumption is compared with the current battery status. If the current battery status is insufficient, the AGV will reject the task and request a transfer to the nearest free charging station [9,10]. For the application of technologies such as AGV and determining the number needed for deployment, static calculations with the alignment of schedules [11] and verification by simulation is required [12]. The simulation allows the dynamic verification of solutions with a view to various interactions that cannot be incorporated into static calculations [13, 14, 15]. The AGV would be irrelevant when disinfecting the premises without the additional superstructure equipment carrying out the disinfection. Currently, ultraviolet (UV) ray disinfection [16, 17, 18] and disinfection by spraying detergent [19] are among the most advanced technologies for disinfection. Today, a wide range of disinfect UV AGV robots have different characteristics for radiation levels as well as the necessary distance from the surface [20,21]. The basic disadvantage of these UV cleaners in the case of the disinfection of surfaces is the period of exposure of human skin to radiation [22]. When spraying disinfectant, this cleaning must take precedence, especially if no one is in the area. On the basis of research [23,24], it is possible to predict that by 2030, there will be a shortage of approximately 15 million workers in the global health sector, even in countries with high incomes. It is therefore necessary to find solutions that will partially improve this situation through the development and expansion of the application of existing technologies [25]. The ability to disinfect the environment, the flexibility [26], and the relatively low cost of performing the function point to the future use of disinfect AGVs in practice. In the future, a significantly higher application of AGVs in the healthcare sector can be expected in a wide range of activities [27]. It is expected that the size of the medical robotics market, which also includes AGVs worldwide, will increase by 31.9 billion from 2022 to 2030 [28]. Compared to classic disinfection by a worker, the efficiency of the application of such devices is comparable.