# Integrated Design Methodology of Automated Guided Vehicles Based on Swarm Robotics
###### Abstract  
In recent years, collaborative robots have become one of the main drivers of Industry 4.0. Compared to industrial robots, automated guided vehicles (AGVs) are more productive, flexible, versatile, and safer. They are used in the smart factory to transport goods. Today, many producers and developers of industrial robots have entered the AGV sector. However, they face several challenges in designing AGV systems, such as the complexity and discontinuity of the design process, as well as the difficulty of defining a decentralized system decision. In this paper, we propose a new integrated design methodology based on swarm robotics to address the challenges of functional, physical, and software integration. This methodology includes two phases: a top-down phase from requirements specification to functional and structural modeling using the systems modeling language (SysML); with a bottom-up phase for model integration and implementation in the robot operating system (ROS). A case study of an automated guided vehicle (AGV) system was chosen to validate our design methodology and illustrate its contributions to the efficient design of AGVs. The novelty of this proposed methodology is the combination of SysML and ROS to address traceability management between the different design levels of AGV systems, in order to achieve functional, physical and software integration. automated guided vehicles (AGV); swarm robotics; smart factory; systems modeling language (SysML); robot operating system (ROS) +
Footnote †: journal: Medicalthe connection between the product and the production system after the product is in operation. Finally, modularity offers the possibility to change parts of a product during production according to the customer's wishes [4]. Collaborative robotics has been considered as one of the enabling technologies of the fourth industrial revolution, within the framework of the Industry 4.0 program [5]. The introduction of such robotic systems in industrial applications poses several problems which cannot be ignored. Nowadays, the use of AGVs in factory logistics is not yet widespread in manufacturing plants. The transport of raw materials and final products is still done by manual forklifts [6]. For this reason, many manufacturers and developers of industrial robots have entered the AGV industry to reduce these problems. However, it is necessary to point out the main obstacles that discourage the industrial sector from integrating AGV systems into their production lines today. The first obstacle is related to communication. In general, AGV systems use wireless communication technology to exchange information between mobile robots, the AGV management system, the fleet management system, and other external elements. This means that everything depends on the quality and robustness of the WiFi connection. However, with the advent of 5G technology, connectivity will theoretically be 10 times higher, and thus 5G will promote the interconnection of all existing networks and technologies, and allow them to communicate with each other more effectively. The second barrier to AGV integration in the industry and particularly smart factories is the problem of making AGVs built by different manufacturers work together. Indeed, different AGV systems do not really speak the same language. We will see later in this paper that the right choice of AGV development methodology and tools could facilitate the collaboration of AGV systems from different manufacturers. The third barrier to AGV integration is related to the limited flexibility of AGVs compared to driver-controlled vehicles. A human operator can react and change his task rapidly. Thus, AGVs are less suitable for non-repetitive tasks. However, if the tasks are repetitive, the choice of the AGV solution could be justified, and this can improve workplace safety. The fourth barrier to integrating AGVs into the production industry is related to the restrictions of the operating environment.