Towards Decentralized Coordination of Multi Robot Systems in Industrial Environments: a Hierarchical Traffic Control Strategy Valerio Digani, Lorenzo Sabattini Cristian Secchi and Cesare Fantuzzi Department of Engineering Sciences and Methods (DISMI) University of Modena and Reggio Emilia via G. Amendola 2, 42122 Reggio Emilia – Italy {valerio.digani, lorenzo.sabattini cristian.secchi, cesare.fantuzzi}@unimore.it Abstract—This paper describes an innovative approach to manage multiple Automated Guided Vehicles (AGVs) in an industrial environment. The proposed approach is based on a two layer architecture for path planning. This architecture consists of a topological layer, composed by macro-cells, and of a route map layer in which the AGVs have to move along fixed paths. The traffic is managed in a decentralized manner. Each AGV computes autonomously its own path both at topological layer and at route map layer. The coordination among the AGVs is based on the negotiation of shared resources. An early phase of validation is provided by the simulation in a structured environment. I. I NTRODUCTION This paper deals with the path planning and coordination of multiple Automated Guided Vehicles (AGVs) in an automated warehouse. Nowadays the AGV solutions for automated warehouses are becoming more and more the standard in addressing the problems of production efficiency and flexibility [1]. Then the number of AGVs is growing more and more and the need to coordinate them in an intelligent way is increasingly at the center of discussions [2]. The standard approach to coordinate a fleet of AGVs lies in a centralized supervisor (the control center) which manages all the information coming form the Warehouse Management System (WMS) and from the environment. The control center handles the coordination of the fleet and the AGVs are managed in order to minimize, or to avoid, the traffic congestion [3]: the optimal path which minimizes a global cost function is searched for each AGV. This paper deals with the research in progress about the navigation of multiple vehicles (AGVs). The paper presents the idea on which the navigation objective of the PAN-Robots project is based. We propose a different approach with respect to the centralized coordination of multiple AGVs currently used in the state of the art [3] [4]. Our idea is based on a hierarchical control architecture [5]. In detail, two layers are used in order to reduce the total complexity and to simplify the control. The first layer is a topological graph of the plant. The global map of the plant is divided into several macro- areas, called sectors. Each sector corresponds to a node of the graph. Its main purpose is to permit a dynamic re-planning of the paths in case of dynamic events. The second layer is the real route map on which the AGVs move. The coordination on the route map is limited only to a single sector of the first layer. In other words, in each sector, the traffic is managed in a decentralized manner on a local route map. The rest of the paper is organized as follows. Section II discusses and provides an overview about the problem of the path planning and coordination for AGVs. Section III describes deeply the addressed problem and the objective. Section IV explains the developed algorithm considering both theoretical and implementation aspects. Finally Section V shows the results of the early phase of validation through virtual simulations and Section VI deals with the conclusions and the next steps of development. II. RELATED WORKS The topic discussed in the paper is related to the path planning of multiple AGVs. First of all, it is important to define the multi-robot path planning problem. This problem is often categorized as centralized or decentral- ized according to the information handling structure among robots (see [6]). The centralized approach is configured to determine the entire path plan for all the robots by a single decision maker. These approaches can theoretically find opti- mal solutions for multi-robot path planning problems [7], but they are restrictive in the number of robots for which they can plan, as the complexity of planning grows exponentially with the number of robots. Thus, while they provide the highest- quality solutions overall, they are generally intractable for large teams. On the other hand, with a decentralized approach, each robot autonomously determines the routes, dissolving the conflicts and collecting information from other robots. Decentralized techniques are generally faster than centralized ones, however they are not complete and may fail to return valid paths for all robots due to deadlocks [5], [8]. Extending the problem still further, centralized approach for generating complete multi-robot path solutions is the work of many researchers. In [7] the path planning algorithm is derived from the principle of optimality. Here the problem of coordinating a multi-robot system is resolved using a coordination space representation of the robot motions. A