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An Architecture for Planning in Embedded Systems

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Abstract

This work is focused on an architecture for systems which act inside an unpredictable world (embedded systems). Several systems dealing with the above issue have been proposed so far. We classify them by means of their architectures and algorithms, obtaining, for example, classical, deferred and reactive planning. From the systems developed up to now, we can point out some of the features that embedded systems must have. Namely, each system must have a flexible architecture, so it can deal with different problems. Each system must allow different basic activities, i.e., actuators and sensors controlling, plan formation and execution, and so on. Each system must have a flexible failure handling mechanism , since no action is guaranteed to succeed. In this paper, we propose a system called MRG which addresses the above features. Its architecture has several modules which can be combined in different ways depending on the problem. A module performs a basic activity. The system is able to detect and to react to failures. The architecture allows MRG a parallel activation of modules and a quick reaction to external events. The control of the architecture is reached by means of a planning language which has a small set of powerful control structures. MRG has been experimented in a complex large-scale application.

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References

  1. P. Agree and D. Chapman, “Pengi: An implementation of a theory of activity,” in Proc. of the 6th National Conf. on Artificial Intelligence, Seattle, WA, 1987, pp. 268-272.

  2. G. Antoniol, B. Caprile, A. Cimatti, and R. Fiutem, “The mobile robot of MAIA: Actions and interactions in a real-life scenario,” in The Biology and Technology of Intelligent Autonomous Agents, Springer Verlag, NATO-ASI Series, 1994. IRST Tech. Rep. 9606-27.

  3. G. Antoniol, B. Caprile, A. Cimatti, R. Fiutem, and G. Lazzari, “Experiencing real-life interaction with the experimental platform of MAIA,” in Proc. of the 1st European Workshop on Human Comfort and Security, 1994. Held in conjunction with EITC'94. Also IRST-Technical Report 9406-27, IRST, Trento, Italy.

  4. A. Armando and E. Giunchiglia, “Embedding complex decision procedures inside an interactive theorem prover,” Annals of Mathematics and Artificial Intelligence, vol. 8, nos.3-4, pp. 475-502, 1993.

    Google Scholar 

  5. A. Armando, A. Cimatti, E. Giunchiglia, P. Pecchiari, L. Spalazzi, and P. Traverso, “Flexible planning by integrating multilevel reasoning,” Journal of Engineering Application of Artificial Intelligence, vol. 4, pp. 401-412, July 1995. Also IRST-Technical Report 9401-10, IRST, Trento, Italy; and DIST Technical Report 93-0016, University of Genova, Italy.

    Google Scholar 

  6. M. Beetz and D. McDermott “Declarative goals in reactive plans,” in Proc. of 1st Int. Conf. on Artificial Intel. Plan. Sys., edited by J. Hendler, Morgan Kaufmann: San Mateo, CA, 1992, pp. 628-638.

    Google Scholar 

  7. S. Benson and N.J. Nilsson, “Reacting, planning and learning in an autonomous agent,” Machine Intelligence, vol. 14, 1995.

  8. S. Biundo, D. Dengler, and J. Köhler, “Deductive planning and plan reuse in a command language environment,” in Proc. 10th European Conf. on Artificial Intelligence, Vienna, Austria, 1992, pp. 628-632.

  9. R.A. Brooks, “A robust layered control system for a mobile robot,” IEEE Journal of Robotics and Automation, vol. 2, no.1, pp. 14-23, 1986.

    Google Scholar 

  10. R. Cattoni, G. Di Caro, M. Aste, and B. Caprile, “Bridging the gap between planning and reactivity: A layered architecture for autonomous indoor navigation,” in Proc. of the the Int. Conf. IROS' 94, Munich, Germany, 1994.

  11. D. Chapman, “Planning for conjunctive goals,” Artificial Intelligence, vol. 32, no.3, pp. 281-331, 1987.

  12. E.W. Dijkstra, “A note on two problems in connexion with graphs,” Numer. Math., vol. 1, pp. 269-271, 1959.

    Google Scholar 

  13. E.H. Durfee and V.R. Lesser, “Incremental planning to control a blackboard-based problem solver,” in Proc. of the 5th National Conf. on Artificial Intelligence, Philadelphia, PA, 1986.

  14. R.E. Fikes and N.J. Nilsson, “STRIPS: A new approach to the application of theorem proving to problem solving,” Artificial Intelligence, vol. 2, nos.3-4, pp. 189-208, 1971.

    Google Scholar 

  15. R.J. Firby, “Building symbolic primitives with continuous control routines,” in Proc. of 1st Int. Conf. on Artificial Intel. Planning Syst., edited by J. Hendler, Morgan Kaufmann: San Mateo, CA, 1992, pp. 62-69.

    Google Scholar 

  16. M. Georgeff, “An embedded reasoning and planning system,” in Proc. from the Rochester Planning Workshop: From Formal Systems to Practical Systems, edited by J. Tenenberg, J. Weber, and J. Allen, Rochester, NY, 1989, pp. 105-128.

    Google Scholar 

  17. M.P. Georgeff, “Situated reasoning and rational behaviour,” Technical Report 21, Australian AI Institute, Carlton, Victoria, Australia, 1991.

    Google Scholar 

  18. M. Georgeff and A.L. Lansky, “Procedural knowledge,” in Proc. of IEEE, 1986, vol. 74, no.10, pp. 1383-1398.

    Google Scholar 

  19. F. Giunchiglia, “GETFOL Manual-GETFOL version 2.0,” Technical Report 92-0010, DIST-University of Genoa, Genoa, Italy, March 1994.

    Google Scholar 

  20. F. Giunchiglia, P. Traverso, A. Cimatti, and L. Spalazzi, “Tactics: Extending the notion plan,” in ECAI-92 Workshop Beyond Sequential Planning, Vienna, Aug. 1992.

  21. F. Giunchiglia, L. Spalazzi, and P. Traverso, “Planning with Failure,” in Proc. 2nd Int. Conf. on AI Planning Systems (AIPS-94), Chicago, 1994.

  22. K.J. Hammond, “Explaining and repairing plans that fail,” Artificial Intelligence, vol. 45, nos.1-2, pp. 173-228, 1990.

    Google Scholar 

  23. S. Hanks and R.J. Firby, “Issues and architectures for planning and execution,” in Proc. of the Workshop on Innovative Approaches to Planning, Scheduling and Control, 1990, pp. 59-70.

  24. B. Hayes-Roth, “A blackboard architecture for control,” Artificial Intelligence, vol. 26, no.3, pp. 251-321, 1985.

    Google Scholar 

  25. L.P. Kaelbling, “An architecture for intelligent reactive systems,” in Reasoning about Actions and Plans: Proc. of the 1986 Workshop, Morgan Kaufmann: San Mateo, CA, 1987.

    Google Scholar 

  26. J.E. Laird, A. Newell, and P.S. Rosenbloom, “Soar: An architecture for general intelligence,” Artificial Intelligence, vol. 33, no.3, pp. 1-4 64, 1987.

    Google Scholar 

  27. D.M. Lyons, “Representing and analyzing action plans as networks of concurrent processes,” IEEE Transactions on Robotics and Automation, vol. 9, no.3, pp. 241-256, June 1990.

    Google Scholar 

  28. N.J. Nilsson, “Teleo-Reactive Programs for Agent Control,” Journal of Artificial Intelligence Research, vol. 1, pp. 139-158, Jan. 1994.

    Google Scholar 

  29. E.H. Ruspini, A. Saffiotti, and K. Konolige, “Progress in reasearch on autonomous vehicle motion,” in Industrial Application of Fuzzy Logics, edited by J. En and R. Langari, 1994.

  30. S. Russel and E. Wefald, “Principles of metareasoning,” in Proc. of the First Int. Conf. on Principles of Knowledge Representation and Reasoning, Toronto, Canada, 1989.

  31. E.D. Sacerdoti, “The nonlinear nature of plans,” in Proc. of the 4th Int. Joint Conf. on Artificial Intelligence, 1975.

  32. A. Saffiotti, K. Konolige, and E.H. Ruspini, “A multivalued logic approach to integrating planning and control,” Artificial Intelligence, vol. 76, nos.1-2, pp. 481-526, 1995.

    Google Scholar 

  33. R. Simmons, “An architecture for coordinating planning, sensing and action,” in Proc. of the Workshop on Innovative Approaches to Planning, Scheduling and Control, 1990, pp. 292-297.

  34. L. Spalazzi, “A planning language for embedded systems,” Internal Report Dec96, Istituto di Informatica, University of Ancona, Italy, 1996.

    Google Scholar 

  35. L. Spalazzi, A. Cimatti, and P. Traverso, “Implementing planning as tactical reasoning,” in Proc. AIS'92, AI Simulation and Planning in High Autonomy Systems Conf., IEEE Computer Society Press: Perth Australia, 1992, pp. 80-85.

    Google Scholar 

  36. M.J. Stefik, “Planning and Meta-Planning,” Artificial Intelligence, vol. 16, no.2, pp. 141-169, 1981.

    Google Scholar 

  37. L. Stringa, “An integrated approach to artificial intelligence: The MAIA Project at IRST,” Technical Report 9103-13, IRST, Trento, Italy, 1991.

    Google Scholar 

  38. P. Traverso, A. Cimatti, and L. Spalazzi, “Beyond the single planning paradigm: Introspective planning,” in Proc. ECAI-92, Vienna, Austria, 1992, pp. 643-647. IRST-Technical Report 9204-05, IRST, Trento, Italy.

  39. P. Traverso and L. Spalazzi, “A logic for acting, sensing and planning,” in Proc. of the 14th Int. Joint Conf. on Artificial Intelligence, 1995. Also IRST-Technical Report 9501-03, IRST, Trento, Italy.

  40. J. van Leeuwen, “Graph Algorithms,” in Handbook of Theoretical Computer Science, edited by J. van Leeuwen, vol. A, North-Holland: Amsterdam, 1990, pp. 526-631.

    Google Scholar 

  41. R. Wilensky, “Meta-planning: Representing and using knowledge about planning in problem solving and natural language understanding,” in Readings in Cognitive Science. A Perspective from Psycology and Artificial Intelligence, edited by A. Collins and E. Smith, Morgan Kaufmann: San Mateo, CA, 1979.

    Google Scholar 

  42. D.E. Wilkins, “Recovering from execution errors in SIPE,” Computational Intelligence, vol. 1, pp. 33-45, 1985.

    Google Scholar 

  43. D.E. Wilkins, Practical Planning: Extending the Classical AI Planning Paradigm, Morgan Kaufmann: San Mateo, CA, 1988.

    Google Scholar 

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  1. Istituto di Informatica, University of Ancona, Via Brecce Bianche, I-60131, Ancona, Italy

    Luca Spalazzi

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  1. Luca Spalazzi
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Spalazzi, L. An Architecture for Planning in Embedded Systems. Applied Intelligence 8, 157–172 (1998). https://doi.org/10.1023/A:1008248208102

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