INTELLIGENT MOBILE MULTI-ROBOTIC SYSTEMS: SOME CHALLENGES AND POSSIBLE SOLUTIONS

Flávio S. Corrêa da Silva, Renata Wassermann, Ana Cristina V. Melo, Leliane N. Barros, Marcelo Finger

Abstract

Intelligent mobile multi-robotic systems (IMMRSs) are coordinated systems of autonomous mobile robots endowed with reasoning capabilities. This sort of systems requires the integrated application of a variety of state-of-the-art techniques developed within the realm of Artificial Intelligence, as well as instigates the further development of different specialisations of Artificial Intelligence. In the present article we examine some of these techniques and specialisations, discuss some specific challenges proposed to the field of Artificial Intelligence by IMMRSs, and suggest possible solutions to these challenges. In order to make our presentation more concrete, we employ throughout the article a specific example of IMMRS application, namely security surveillance of an empty building by a team of robots.

References

  1. A. G. Andrade, A. C. V. Melo, and M. M. Amorim. Da especificao verificao de agentes mveis - um ambiente grfico. In Mauricio Solar and David Fernandez Baca, editors, Anales de 30th Conferencia Latino Americana de Informtica, Arequipa, Peru. 2004.
  2. L. N. de Barros and E. Iamamoto. Planning for tasks in cognitive robotics. Proceedings of VI Simpsio Brasileiro de Automao Inteligente, Bauru, SP, Brazil. 2003.
  3. C. P. Campos, and F. G. Cozman. Inference in credal networs using multilinear programming. Second Starting AI Researcher Symposium (STAIRS), 50-61, IOS Press. 2004.
  4. J. Cantwell. A formal model of multi-agent beliefinteraction. Journal of Logic, Language and Information. 2005. to appear.
  5. M.-H. Chen, and H. M. Kao. Testing object-oriented programs - an integrated approach. In Proceedings of the Tenth International Symposium on Software Reliability Engineering. IEEE Computer Society Press. 1999.
  6. S. Chopra, R. Parikh and R. Wassermann. Approximate belief revision. Logic Journal of the IGPL, 9(6):755- 768. 2001.
  7. F. S. Correa da Silva. Where am I? Where are you? Technical Report 2005-03. Department of Computer Science, University of Sao Paulo. 2005.
  8. M. Dalal. Anytime families of tractable propositional reasoners. In International Symposium of Artificial Intelligence and Mathematics AI/MATH-96, pages 42-45. 1996.
  9. J. Dix, M. Nanni, and V. S. Subrahmanian. Probabilistic agent programs. ACM Transactions on Computational Logic, v. 1(2), 207-245. 2000.
  10. M. Finger. Polynomial approximations of full propositional logic via limited bivalence. In 9th European Conference on Logics in Artificial Intelligence (JELIA 2004), LNAI vol. 3229, pages 526-538. 2004.
  11. M. Finger and R. Wassermann. Expressivity and control in limited reasoning. In Frank van Harmelen, editor, 15th European Conference on Artificial Intelligence (ECAI02), pages 272-276, Lyon, France. 2002.
  12. M. Finger and R. Wassermann. Approximate and limited reasoning: Semantics, proof theory, expressivity and control. Journal of Logic And Computation, 14(2):179 - 204. 2004.
  13. M. Finger and R. Wassermann. The universe of propositional approximations. Theoretical Computer Science. 2005. to appear.
  14. A. Gabaldon. Programming hierarchical task networks in the situation calculus. AIPS-2002 Workshop on On-line Planning and Scheduling. Toulouse, France. 2002.
  15. P. Gärdenfors. Knowledge in Flux - Modeling the Dynamics of Epistemic States. MIT Press. 1988.
  16. J. Gasos, and A. Saffiotti. Using fuzzy sets to represent uncertain spatial knowledge in autonomous robots. Spatial Cognition and Computation, v. 1, 205-226, Kluwer. 1999.
  17. B. P. Gerkey, S. Thrun, and G. Gordon. Visibility-based pursuit-evasion with limited field of view. In Proceedings of the National Conference on Artificial Intelligence (AAAI 2004). AAAI Press. 2004.
  18. S. O. Hansson. A Textbook of Belief Dynamics. Kluwer Academic Press. 1999.
  19. E. Iamamoto. HTN Planning in Golog. Msc Dissertation at the Departament of Computer Science of the University of So Paulo, Brazil. 2005.
  20. J. S. Ide, and F. G. Cozman. IPE and L2U: Approximate algorithms for credal networks. Second Starting AI Researcher Symposium (STAIRS), 118-127, IOS Press. 2004.
  21. D. Kung, N. Suchak, P. Hsia, Y. Toyoshima, and C. Chen. Object state testing for object-oriented programs. In Proc. of COMPSAC'95. IEEE Computer Society Press. 1995.
  22. E. Kutluhan, J. Hendler, and D. Nau. Complexity, decidability and undecidability results for domain-independent planning. Artificial Intelligence 76(1-2):75-88. 1995.
  23. H. J. Levesque, R. Reiter, Y. Lesprance, F. Lin, and R. B. Scherl. Golog: A logic programming language for dynamic domains. 1997.
  24. F. Massacci. A proof theory for tractable approximations of propositional reasoning. In Maurizio Lenzerini, editor, AI*IA-97, volume 1321 of LNAI, pages 219-230. SV. 1997.
  25. J. McCarthy. Situations, actions and causal laws, Technical report, Stanford University. Reprinted in Semantic Information Processing (M. Minsky ed.), MIT Press, Cambridge, MAss., 1968, pp. 410-417. 1963.
  26. J. D. McGregor, and T. D. Korson. Integrated objectoriented testing and development processes. Communications of ACM, 37(9). 1994.
  27. A. C. V. Melo. From active names to pi-calculus rewriting rules. ENTCS (Electronic Notes in Theoretical Computer Science), to appear. 2005.
  28. A. C. V. Melo. p-calculus rewriting rules based on active names. In Alexandre Mota and Arnaldo Moura, editors, SBMF2004: 7th Brazilian Symposium on Formal Methods, Recife, PE, Brazil. 2004.
  29. A. C. V. Melo. A study on the potential active names of p- agents. ENTCS (Electronic Notes in Theoretical Computer Science), 95(C):269-286. 2004.
  30. A. C. V. Melo. A study on the potential active names of p- agents. In A. L. C. Cavalcanti and Patrcia Machado, editors, WMF2003: 6th Brazilian Workshop on Formal Methods, Campina Grande, PB, Brazil. 2003.
  31. R. Milner. Communication and Concurrency. PrenticeHall, first edition. 1989.
  32. R. Milner. Communicating and Mobile Systems: the p- Calculus. Cambridge University Press. 1999.
  33. R. Ng, and V. S. Subrahmanian. Probabilistic logic programming. Information and Computation, v. 101(2), 150-201. 1992.
  34. N. Nilsson. Probabilistic logic. 28(1):71-87. 1986.
  35. Artificial Intelligence, P. R. Nunes and A. C. V. Melo. Ocongra - uma ferramenta para gerao de grafos de controle de fluxo de objetos. In Murilo Camargo and Jaelson Castro, editors, Anais do Simpsio Brasileiro de Engenharia de Software, Braslia, Brasil. 2004.
  36. S. L. Pereira and L. N. Barros. High-Level Robot Programs Based on Abductive Event Calculus. International Workshop on Cognitive Robotics, CogRob2002. 2002.
  37. S. L. Pereira and L. N. Barros. Formalizing planning algorithms: a logical framework for the research on extending the classical planning approach. International Conference on Planning Systems Workshop: Connecting Planning Theory with Practice. 2004.
  38. S. L. Pereira and L. N. Barros. Planning with Abduction: a logical framework to explore extensions to classical planning. Simpsio Brasileiro de Inteligncia Artificial, LNAI. 2004.
  39. S. L. Pereira and L. N. Barros. High-level Robot Programming: an abductive approach using event calculus. Simpsio Brasileiro de Inteligncia Artificial, LNAI. 2004.
  40. R. Reiter. Knowledge in Action: Logical Foundations for Specifying and Implementing Dynamical Systems. MIT Press. 2001.
  41. J. Riani. Towards an efficient inference procedure through syntax based relevance. Master's thesis, Department of Computer Science, University of Sa˜o Paulo. 2004. Available at http://www.ime.usp.br/˜joselyto/mestrado.
  42. J. Riani and R. Wassermann. Using relevance to speed up inference - some empirical results. In Proceedings of the Brazilian Artificial Intelligence Symposium, Lecture Notes on Artificial Intelligence. Springer-Verlag. 2004.
  43. J. C. F. Rocha, and F. G. Cozman. Inference in credal networks with branch-and-bound algorithms. Third International Symposium on Imprecise Probabilities and Their Applications, 482-495, Carleton Scientific. 2003.
  44. J. W. Roorda, W. Van der Hoek, and J. J. Meyer. Iterated belief change in multi agent systems. Logic Journal of the IGPL, 11(2):223-246. 2003.
  45. A. Saffiotti. Handling uncertainty in control of autonomous robots. in Wooldridge, M., Veloso, M. (eds.) Artificial Intelligence Today, 381-408, Springer-Verlag. 1999.
  46. M. Schaerf and M. Cadoli. Tractable reasoning via approximation. Artificial Intelligence, 74(2):249-310. 1995.
  47. F. W. Trevizan and L. N. de Barros. Planejamento e Execuo em Golog para Robs Lego Mindstorm. Encontro Nacional de Inteligncia Artificial. 2005.
  48. R. Wassermann. Resource-Bounded Belief Revision. PhD thesis, Institute for Logic, Language and Computation - University of Amsterdam. 1999.
  49. R. Wassermann. On structured belief bases. In Hans Rott and Mary-Anne Williams, editors, Frontiers in Belief Revision. Kluwer. 2001.
  50. E. J. Weyuker. The evaluation of program-based software test data adequacy. Communications of ACM, 31(6). 1988.
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Paper Citation


in Harvard Style

S. Corrêa da Silva F., Wassermann R., Cristina V. Melo A., N. Barros L. and Finger M. (2005). INTELLIGENT MOBILE MULTI-ROBOTIC SYSTEMS: SOME CHALLENGES AND POSSIBLE SOLUTIONS . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 972-8865-30-9, pages 479-485. DOI: 10.5220/0001190904790485


in Bibtex Style

@conference{icinco05,
author={Flávio S. Corrêa da Silva and Renata Wassermann and Ana Cristina V. Melo and Leliane N. Barros and Marcelo Finger},
title={INTELLIGENT MOBILE MULTI-ROBOTIC SYSTEMS: SOME CHALLENGES AND POSSIBLE SOLUTIONS},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2005},
pages={479-485},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001190904790485},
isbn={972-8865-30-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - INTELLIGENT MOBILE MULTI-ROBOTIC SYSTEMS: SOME CHALLENGES AND POSSIBLE SOLUTIONS
SN - 972-8865-30-9
AU - S. Corrêa da Silva F.
AU - Wassermann R.
AU - Cristina V. Melo A.
AU - N. Barros L.
AU - Finger M.
PY - 2005
SP - 479
EP - 485
DO - 10.5220/0001190904790485