In this paper we address the problem of assigning a set of tasks to a set of Automated Guided Vehicles (AGVs), in a conflict-free manner. Specifically, we consider a system of multiple AGVs, moving along a predefined roadmap, and utilized for transportation of goods in automated warehouses. Sequential application of task assignment and path planning often gives rise to pathological situations, such as deadlocks, in which AGVs block each other, thus preventing tasks completion. In this paper we propose a method for assigning tasks while taking into account the subsequent path planning, encoding possible conflicts into a conflict graph, that is subsequently utilized for defining constraints of an optimization problem. Simulations are performed on maps of real industrial environments, to compare the proposed method with traditional task assignment.

Optimized simultaneous conflict-free task assignment and path planning for multi-AGV systems / Sabattini, L., Digani, V., Secchi, C., Fantuzzi, C.. - 2017-:(2017), pp. 1083-1088. (2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017 can 2017) [10.1109/IROS.2017.8202278].

Optimized simultaneous conflict-free task assignment and path planning for multi-AGV systems

Sabattini, Lorenzo;Digani, Valerio;Secchi, Cristian;Fantuzzi, Cesare
2017

Abstract

In this paper we address the problem of assigning a set of tasks to a set of Automated Guided Vehicles (AGVs), in a conflict-free manner. Specifically, we consider a system of multiple AGVs, moving along a predefined roadmap, and utilized for transportation of goods in automated warehouses. Sequential application of task assignment and path planning often gives rise to pathological situations, such as deadlocks, in which AGVs block each other, thus preventing tasks completion. In this paper we propose a method for assigning tasks while taking into account the subsequent path planning, encoding possible conflicts into a conflict graph, that is subsequently utilized for defining constraints of an optimization problem. Simulations are performed on maps of real industrial environments, to compare the proposed method with traditional task assignment.
2017
no
Inglese
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017
can
2017
IEEE International Conference on Intelligent Robots and Systems
2017-
1083
1088
9781538626825
Institute of Electrical and Electronics Engineers Inc.
345 E 47TH ST, NEW YORK, NY 10017 USA
Control and Systems Engineering; Software; 1707; Computer Science Applications1707 Computer Vision and Pattern Recognition
Sabattini, Lorenzo; Digani, Valerio; Secchi, Cristian; Fantuzzi, Cesare
Atti di CONVEGNO::Relazione in Atti di Convegno
273
4
Optimized simultaneous conflict-free task assignment and path planning for multi-AGV systems / Sabattini, L., Digani, V., Secchi, C., Fantuzzi, C.. - 2017-:(2017), pp. 1083-1088. (2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017 can 2017) [10.1109/IROS.2017.8202278].
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info:eu-repo/semantics/conferenceObject
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1156954
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