This paper presents an optimization strategy to coordinate multiple Autonomous Guided Vehicles (AGVs) on ad-hoc pre-defined roadmaps used in logistic operations in industrial applications. Specifically, the objective is to maximize traffic throughput of AGVs navigating in an automated warehouse by minimizing the time AGVs spend negotiating complex traffic patterns to avoid collisions with other AGVs. In this work, the coordination problem is posed as a Quadratic Programming (QP) problem where the optimization is performed in a centralized manner. The optimality of the coordination strategy is established and the feasibility of the strategy is validated in simulation for different scenarios and for real industrial environments. The performance of the proposed strategy is then compared with a decentralized coordination strategy which relies on local negotiations for shared resources. The results show that the proposed coordination strategy successfully maximizes vehicle throughout and significantly minimizes the time vehicles spend negotiating traffic under different scenarios.

A Quadratic Programming approach for coordinating multi-AGV systems / Digani, Valerio; Hsieh, M. Ani; Sabattini, Lorenzo; Secchi, Cristian. - (2015), pp. 600-605. ((Intervento presentato al convegno 11th IEEE International Conference on Automation Science and Engineering, CASE 2015 tenutosi a Gothenburg, Sweden nel 24-28 August 2015 [10.1109/CoASE.2015.7294144].

A Quadratic Programming approach for coordinating multi-AGV systems

SABATTINI, Lorenzo;SECCHI, Cristian
2015

Abstract

This paper presents an optimization strategy to coordinate multiple Autonomous Guided Vehicles (AGVs) on ad-hoc pre-defined roadmaps used in logistic operations in industrial applications. Specifically, the objective is to maximize traffic throughput of AGVs navigating in an automated warehouse by minimizing the time AGVs spend negotiating complex traffic patterns to avoid collisions with other AGVs. In this work, the coordination problem is posed as a Quadratic Programming (QP) problem where the optimization is performed in a centralized manner. The optimality of the coordination strategy is established and the feasibility of the strategy is validated in simulation for different scenarios and for real industrial environments. The performance of the proposed strategy is then compared with a decentralized coordination strategy which relies on local negotiations for shared resources. The results show that the proposed coordination strategy successfully maximizes vehicle throughout and significantly minimizes the time vehicles spend negotiating traffic under different scenarios.
11th IEEE International Conference on Automation Science and Engineering, CASE 2015
Gothenburg, Sweden
24-28 August 2015
600
605
Digani, Valerio; Hsieh, M. Ani; Sabattini, Lorenzo; Secchi, Cristian
A Quadratic Programming approach for coordinating multi-AGV systems / Digani, Valerio; Hsieh, M. Ani; Sabattini, Lorenzo; Secchi, Cristian. - (2015), pp. 600-605. ((Intervento presentato al convegno 11th IEEE International Conference on Automation Science and Engineering, CASE 2015 tenutosi a Gothenburg, Sweden nel 24-28 August 2015 [10.1109/CoASE.2015.7294144].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1113371
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