Decentralized control of automatic guided vehicles: applying multi-agent systems in practice

ABSTRACT

An automatic guided vehicle (AGV) transportation system is a fully automated system that provides logistic services in an industrial environment such as a warehouse or a factory. Traditionally, the AGVs that execute the transportation tasks are controlled by a central server via wireless communication. In a joint effort between Egemin, an industrial manufacturer of AGV transportation systems, and DistriNet Labs research at the Katholieke Universiteit Leuven, we developed an innovative decentralized architecture for controlling AGVs. The driving motivations behind decentralizing the control of AGVs were new and future quality requirements such as flexibility and openness. At the software architectural level, the AGV control system is structured as a multi-agent system; the detailed design and implementation is object-oriented. In this paper, we report our experiences with developing the agent-based control system for AGVs. Starting from system requirements, we give an overview of the software architecture and we zoom in on a number of concrete functionalities. We reflect on our experiences and report lessons learned from applying multi-agent systems for real-world AGV control.

REFERENCES

• 1: M. Barbacci, R. Ellison, A. Lattanze, J. Stafford, C. Weinstock, and W. Wood. Quality Attribute Workshops. Technical Report CMU/SEI-2003-TR-016, Software Engineering Institute, Carnegie Mellon University, PA, USA, 2003.
• 2: Paul Clements , Rick Kazman, Software Architecture in Practices, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 2003
• 3: A. Nelis Boucké, Danny Weyns, Kurt Schelfthout, and Tom Holvoet. Applying the ATAM to an architecture for decentralized control of a transportation system. In phSecond International Conference on Quality of Software Architectures, volume 4214 of Lecture Notes in Computer Science, Springer, 2006.
• 4: Felia Buchmann , Len Bass, Introduction to the attribute driven design method, Proceedings of the 23rd International Conference on Software Engineering, p.745-746, May 12-19, 2001, Toronto, Ontario, Canada
• 5: Stefan Bussmann , Nicolas R. Jennings , Michael Wooldridge, Multiagent Systems for Manufacturing Control, SpringerVerlag, 2004
• 6: Evaluating software architectures: methods and case studies, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 2001
• 7: Edmund H. Durfee , Victor R. Lesser, Negotiating task decomposition and allocation using partial global planning, Distributed Artificial Intelligence (Vol. 2), Morgan Kaufmann Publishers Inc., San Francisco, CA, 1989
• 8: B. Henderson--Sellers and P. Giorgini. Agent-oriented Methodologies. Idea Group Inc., 2005.
• 9: Jeff Kramer , Jeff Magee, Self-Managed Systems: an Architectural Challenge, 2007 Future of Software Engineering, p.259-268, May 23-25, 2007 [doi>10.1109/FOSE.2007.19]
• 10: D. L. Parnas, Designing Software for Ease of Extension and Contraction, IEEE Transactions on Software Engineering, v.5 n.2, p.128-138, March 1979 [doi>10.1109/TSE.1979.234169]
• 11: Jeffrey Richter , Jeffrey Richter, Applied Microsoft .NET Framework Programming, Microsoft Press, Redmond, WA, 2002
• 12: K. Schelfthout. Supporting Coordination in Mobile Networks: A Middleware Approach. Ph.D, Katholieke Universiteit Leuven, 2006.
• 13: Kurt Schelfthout , Danny Weyns , Tom Holvoet, Middleware for Protocol-Based Coordination in Mobile Applications, IEEE Distributed Systems Online, v.7 n.8, p.1, August 2006 [doi>10.1109/MDSO.2006.50]
• 14: R. G. Smith, The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver, IEEE Transactions on Computers, v.29 n.12, p.1104-1113, December 1980 [doi>10.1109/TC.1980.1675516]
• 15: E. Steegmans, D. Weyns, T. Holvoet, and Y. Berbers. A Design Process for Adaptive Behavior of Situated Agents. In Agent-Oriented Software Engineering V, volume 3382 of Lecture Notes in Computer Science, Springer, 2005.
• 16: K. Sycara. Multiagent Systems. Artificial Intelligence, 10 (2): 79--93, 1998.
• 17: T. Tyrrell. Computational Mechanisms for Action Selection. PhD Dissertation, University of Edinburgh, 1993.
• 18: D. Weyns. An Architecture-Centric Approach for Software Engineering with Situated Multiagent Systems. Ph.D, Katholieke Universiteit Leuven, 2006.
• 19: Danny Weyns , Tom Holvoet, Architectural design of a situated multiagent system for controlling automatic guided vehicles, International Journal of Agent-Oriented Software Engineering, v.2 n.1, p.90-128, January 2008 [doi>10.1504/IJAOSE.2008.016801]
• 20: Danny Weyns , Kurt Schelfthout , Tom Holvoet , Tom Lefever, Decentralized control of E'GV transportation systems, Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, July 25-29, 2005, The Netherlands [doi>10.1145/1082473.1082806]
• 21: Danny Weyns , Nelis Boucké , Tom Holvoet, A field-based versus a protocol-based approach for adaptive task assignment, Autonomous Agents and Multi-Agent Systems, v.17 n.2, p.288-319, October 2008 [doi>10.1007/s10458-008-9037-x]
• 22: Michael Wooldridge , Nicholas R. Jennings , David Kinny, The Gaia Methodology for Agent-Oriented Analysis and Design, Autonomous Agents and Multi-Agent Systems, v.3 n.3, p.285-312, September 2000 [doi>10.1023/A:1010071910869]

INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
        D.2.11 Software Architectures
            Subjects: Patterns (e.g., client/server, pipeline, blackboard)

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Multiagent systems

General Terms:
Design

Keywords:
AGV, automatic guided vehicle, decentralized control, multi-agent system, software architecture