# Synchronization of Heterogeneous Multi-Robotic Cell with Emphasis on Low Computing Power
## 1 Introduction  
A current significant challenge for industrial production is vision substantiation of a future factory within the concept of Industry 4.0, with the aid of the Internet of Things (IoT) concept. The implementation of this concept into production requires high flexibility and adaptability of production lines and their smaller units. The deployment of this concept in practice is widely supported in Germany, and the first solutions in isolated production systems were developed there [1, 2]. [PERSON] et al. [3] note that the Internet of Things is a well-known concept that represents the next generation of products and communication among them. It has a direct correlation with the Industry 4.0 standard, where the existence of smart products is one of the prerequisites for intelligent manufacturing implementation [4]. In a smart factory, individual customer orders determine manufacturing processes and the associated supply chains. This results in the need for high production flexibility with shorter production times, which require the implementation of measures to improve production efficiency, often at a low cost associated with solving these problems. The new term \"smart factory\" is introduced here to refer to the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of Things, and cloud computing, as declared by [PERSON] et al. [5], [PERSON] [6], and [PERSON] et al. [7]. One of the important indicators for such productionis decentralized decision making, that is, the ability of equipment to make its own decisions, which are the most independent inside closed production complexes. In the case of essential decisions and conflicts, it is clearly necessary to assign tasks to the next level of production control [5]. Closed production complexes require continuity of individual manufacturing operations, synchronization of individual production facilities, and the possibility of rapid adaptation and production time changes of individual production facilities, depending on the control structure of such complexes. An alternative deployment area of robotic manipulators with a potential requirement for synchronization of their activities is healthcare, particularly that related to the rehabilitation of patients. Techniques dealing with robot-assisted therapy are included, for example, in the works of authors [PERSON] and [PERSON] or [PERSON] et al. [8; 9]. Various methods of synchronization and control of individual production operations and processes are currently used. It is necessary to differentiate whether these are autonomous mobile systems or manipulators and what usage is expected of them. Many published works deal with the synchronization of mobile platform activities. [PERSON] et al. [10] offer a solution for the synchronization of a large group of mobile robots as an open-source, low cost robot, designed to test collective algorithms on hundreds or thousands of robots accessible to robotics researchers. This solution allows for easier testing of algorithms designed to control robot groups because these control algorithms, due to their cost, time, and complexity, are confirmed only through simulations. Popular synchronization methods are also based on the observation of nature, for example, fireflies as presented by [PERSON] et al. [11]. A modification of this approach is intended to operate on systems that use a communication channel where contention and delays are possible. In addition, the coordination mechanisms that enable the execution of cooperative tasks with modular robotic systems are presented in the contribution of [PERSON] et al. [12]. They describe the implementation of a tight cooperation strategy through Intra M-Robot communication based on a closed-loop discrete time method and the remote clock across the robot configuration enables proper coordination inside the colony.