In this paper we consider the problem of coordinating the motion of a group of Automated Guided Vehicles (AGVs) utilized in industrial environments for logistics operations. In particular, we consider a hierarchical coordination strategy, where the environment is partitioned into sectors: coordination on the top layer defines the sequence of sectors to be traveled, while coordination on the bottom layer deals with traffic management inside each sector. In this paper we introduce a novel partitioning algorithm, that defines the sectors in a dynamic manner, taking into account both the shape of the (generally non-convex) environment, and the current distribution of the AGVs. This is achieved exploiting a clustering algorithm, and subsequently defining the sectors based on the geodesic distance.
Hierarchical coordination strategy for multi-AGV systems based on dynamic geodesic environment partitioning / Sabattini, Lorenzo; Digani, Valerio; Secchi, Cristian; Fantuzzi, Cesare. - 2016-:(2016), pp. 4418-4423. (Intervento presentato al convegno 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 tenutosi a Daejeon Convention Center, kor nel 2016) [10.1109/IROS.2016.7759650].
Hierarchical coordination strategy for multi-AGV systems based on dynamic geodesic environment partitioning
Sabattini, Lorenzo;Digani, Valerio;Secchi, Cristian;Fantuzzi, Cesare
2016
Abstract
In this paper we consider the problem of coordinating the motion of a group of Automated Guided Vehicles (AGVs) utilized in industrial environments for logistics operations. In particular, we consider a hierarchical coordination strategy, where the environment is partitioned into sectors: coordination on the top layer defines the sequence of sectors to be traveled, while coordination on the bottom layer deals with traffic management inside each sector. In this paper we introduce a novel partitioning algorithm, that defines the sectors in a dynamic manner, taking into account both the shape of the (generally non-convex) environment, and the current distribution of the AGVs. This is achieved exploiting a clustering algorithm, and subsequently defining the sectors based on the geodesic distance.Pubblicazioni consigliate
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