An Agent-based Model of Autonomous Automated-Guided Vehicles for Internal Transportation in Automated Laboratories

Lluís Ribas-Xirgo, Ismael F. Chaile

Abstract

Agent-based modelling enables simulating complex systems and controlling them, as well. In the industrial domain there are plenty of these systems not only because of the size but also because of the need for fault-tolerance and adaptability. Typically, these cases are solved by dividing systems into different dimensions, including the transportation one. In this paper, we take this approach to build a framework to develop and control transportation in applications within the industrial domain, which will be tested on an automated laboratory. The framework is based on a multi-agent simulator that contains the model of the plant with transportation agents having a multi-layered architecture. The lower-level layers correspond to those that would be embedded into physical transportation agents. Therefore, while agents communicate to each other within the simulator environment, communication between upper-level layers and lower-lever layers of each agent is done internally for the simulated parts and externally for the real counterparts. The simulator can be used stand-alone to functionally validate a system or in combination with real agents as a monitoring/controlling tool. Preliminary results prove the viability of the framework as a design tool and show the difficulties to work with physical agents.

References

  1. Armendáriz, M., Burguillo, J.C., Peleteiro, A., Arnould, G., Khadraoui, D. (2011). Carpooling: A multiagent simulation in Netlogo. In Proc. of the 25th European Conf. on Modelling and Simulation (ECMS), Krakow (Poland).
  2. Davidsson, P., Henesey, L., Ramstedt, L., Törnquist, J., Wernstedt, F. (2005). An analysis of agent-based approaches to transport logistics. In Transportation Research Part C 1. 255-271.
  3. De Wolf, T., Holvoet, T. (2003). Towards Autonomic Computing: Agent-Based Modelling, Dynamical Systems Analysis, and Decentralised Control. In Proc. of the First Int'l. Workshop on Autonomic Computing Principles and Architectures.
  4. Fernández-Caballero, A., Gascueña, J.M. (2009). Developing Multi-Agent Systems through Integrating Prometheus, INGENIAS and ICARO-T. In Proc. of Int'l. Conf. on Agents and Artificial Intelligence (ICAART).
  5. Himoff, J., Rzevski, G., Hinton, M., Skobelev, P. (2006). MAGENTA Technology: Multi-Agent Logistics iScheduler for Road Transportation. In Proc. of AAMAS, Hokkaido (Japan).
  6. Kashif, A., Binh Le., X.H., Dugdale, J., Ploix, S. (2011). Agent-based framework to simulate inhabitants' behaviour in domestic settings for energy management. In Proc. of Int'l. Conf. on Agents and Artificial Intelligence (ICAART).
  7. Mathieu, P., Secq, Y. (2012). Environment Updating and Agent Scheduling Policies in Agent-based Simulators. In Proc. of Int'l. Conf. on Agents and Artificial Intelligence (ICAART), 170-175.
  8. Ribas-Xirgo, Ll., Miró-Vicente, A., Chaile, I. F., VelascoGonzález, A. J. (2012). Multi-Agent Model of a Sample Transport System for Modular In-Vitro Diagnostics Laboratories. In Proc. of Emerging Technologies and Factory Automation (ETFA), Krakow (Poland).
  9. Santa-Eulalia, L.A., Halladjian, G., D'Amours, S., Frayret, J.-M. (2011). Integrated methodological frameworks for modeling agent-based advanced supply chain planning systems: A systematic literature review. In J. Ind. Eng. & Management, JIEM, 2011 - 4(4):624-668.
  10. Schreiber, S., Fay, A. (2011). Requirements for the benchmarking of decentralized manufacturing control systems. In Proc. of Emerging Technologies and Factory Automation (ETFA).
  11. Wojtusiak, J., Warden, T., Herzog, O. (2011). Agentbased Pickup and Delivery Planning: The Learnable Evolution Model Approach. In Proc. of Int'l. Conf. on Complex, Intelligent and Software Intensive Systems (CISIS), 1-8.
Download


Paper Citation


in Harvard Style

Ribas-Xirgo L. and Chaile I. (2013). An Agent-based Model of Autonomous Automated-Guided Vehicles for Internal Transportation in Automated Laboratories . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8565-38-9, pages 262-268. DOI: 10.5220/0004257702620268


in Bibtex Style

@conference{icaart13,
author={Lluís Ribas-Xirgo and Ismael F. Chaile},
title={An Agent-based Model of Autonomous Automated-Guided Vehicles for Internal Transportation in Automated Laboratories},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2013},
pages={262-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004257702620268},
isbn={978-989-8565-38-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - An Agent-based Model of Autonomous Automated-Guided Vehicles for Internal Transportation in Automated Laboratories
SN - 978-989-8565-38-9
AU - Ribas-Xirgo L.
AU - Chaile I.
PY - 2013
SP - 262
EP - 268
DO - 10.5220/0004257702620268