# Implementation of Autonomous Mobile Robot in SmartFactory
## 1 Introduction  
In general, robots for industry purposes were introduced in 1961 to achieve increasing elaborate tasks. They occur in tedious and repetitive tasks such as welding, painting, moving, or cutting with incredible precision [1, 2, 3, 4]. These classic commercial robots suffer from a fundamental disadvantage, a lack of mobility. In contrast, mobile robots were introduced to be able to travel throughout the manufacturing plant to help flexibly with manufacturing processes. Fixed robots or robotic manipulators commonly operate in zones where humans cannot go. Rather, mobile robots share space with humans in human environments and act like cobots. These robots are not developed for mobility reasons, but due to their autonomy, their ability to maintain a sense of position and navigate without human intervention is paramount [2, 5]. This work is focused on the application of autonomous industrial mobile robots (AMR). It is still a relatively new technology that is gradually finding use in industry, but also in other sectors [2, 6, 7]. The biggest advantages of autonomous robots include their independence and ability to orient themselves in space, without the need for external guidelines or other elements in the environment. Autonomous mobile robots orient themselves with the help of advanced sensors [8, 9] and a virtual space map. They can be used in the fields of storage, transport, and production [1, 10, 11, 12]. [PERSON] and their colleague presented in their review paper [13] the results of many research papers focused on precise robot navigation. This problem is not solved yet and it depends on many factors. Most problems occur due to processing time or position and direction estimation. Furthermore, research on planning algorithms [14, 15] is still in progress and many researchers have also been testing different types of modern sensors for sensing the map and the actual position of the robot in the space in combination with the simulation [16, 17]. In this paper, we demonstrate a real cooperation between an AMR and SmartFactory [18]. The study was carried out using a commercial AMR from Mobile Industrial Robots (MiR), a centralized control station for MiR robots (MiR FLEET), andan I/O module for MiR robots (MiR WISE) to create communication between them. Virtual maps and software (tasks) were created to enable us to experiment. The problem was the narrow space and the need for a precise approach of the robot to the SmartFactory premises. Several types of precise markers were used in the experiment. The result was different accuracies of the entrances. The autonomous mobile robots were then suitably complemented by the actual implementation of the camera surveillance system. This allowed the operator to always have an overview of the actual conditions around the robot. The MiR autonomous mobile robots were chosen for the application. These mobile robotic platforms are ready for the industrial environment and are equipped with a combination of laser sensors, ultrasonic sensors, and cameras. Together, they allow robots to move safely around the environment and be able to respond to most types of obstacles [19]. It was also necessary to analyze the functions and behavior of the SmartFactory production line and then design suitable implementations of an autonomous mobile robot. The line produced a pair of products, each of them having a different target location, and, for this reason, a pair of mobile robot implementations, the so-called tasks, was designed. The MiR100 mobile robot was used to operate the production line. The main objective of this paper was to provide an analysis of the accuracy of the position findings of autonomous mobile robots using marker labeling. This was demonstrated through an example of an application that links an autonomous mobile robot to SmartFactory. The novelty of the paper is the experiment with different types of markers to get the most accurate position of the robot in the production line and its statistical evaluation.