The Artificial Ecosystem: A Multiagent Architecture

  • Maurizio Miozzo
  • Antonio Sgorbissa
  • Renato Zaccaria
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2690)


We propose a multiagent, distributed approach to autonomous mobile robotics which is an alternative to most existing systems in literature: robots are thought of as mobile units within an intelligent environment where they coexist and co-operate with fixed, intelligent devices that are assigned different roles: helping the robot to localize itself, controlling automated doors and elevators, detecting emergency situations, etc. To achieve this, intelligent sensors and actuators (i.e. physical agents) are distributed both onboard the robot and throughout the environment, and they are handled by Real-Time software agents which exchange information on a distributed message board. The paper describes the approach and shows the details of its implementation, by outlining the benefits in terms of efficiency and Real-Time responsiveness.


Mobile Robot Message Board Intelligent Environment Landmark Position Smooth Trajectory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Brooks, R.: A Robust Layered Control System for a mobile robot. IEEE J. of Robotics and Automation RA-2 l (1986)Google Scholar
  2. 2.
    Parker, L.E.: ALLIANCE: An Architecture for Fault Tolerant Multi-Robot Cooperation. IEEE Transactions on Robotics and Automation 14(2) (1998)Google Scholar
  3. 3.
    Arkin, R.C.: Motor Schema-Based Mobile Robot Navigation. International Journal of Robotics Research (1990)Google Scholar
  4. 4.
    Gat, E.: Integrating Planning and Reacting in a Heterogeneous Asynchronous Architecture for Controlling Real-World Mobile Robots. In: Proceedings of the National Conference on Artificial Intelligence. AAAI, Menlo Park (1992)Google Scholar
  5. 5.
    Burgard, W., Cremers, A.B., Fox, D., Hähnel, D., Lakemeyer, G., Schulz, D., Steiner, W., Thrun., S.: Experiences with an interactive museum tour-guide robot. Artificial Intelligence (AI) 114(1–2) (2000)Google Scholar
  6. 6.
    Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs (1995)zbMATHGoogle Scholar
  7. 7.
    Piaggio, M., Sgorbissa, A., Zaccaria, R.: Pre-emptive Versus Non Pre-emptive Real Time Scheduling in Intelligent Mobile Robotics. Journal of Experimental and Theoretical Artificial Intelligence 2(12) (2000)Google Scholar
  8. 8.
    Piaggio, M., Zaccaria, R.: An Autonomous System for a Vehicle Navigating in a Partially or Totally Unknown Environment. In: Proc. Int. Workshop on Mechatronical Computer Systems for Perception and Action, MCPA, Pisa, Italy (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Maurizio Miozzo
    • 1
  • Antonio Sgorbissa
    • 1
  • Renato Zaccaria
    • 1
  1. 1.DISTUniversity of Genoa

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