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Answer set programming for collaborative housekeeping robotics: representation, reasoning, and execution

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Abstract

Answer set programming (ASP) is a knowledge representation and reasoning paradigm with high-level expressive logic-based formalism, and efficient solvers; it is applied to solve hard problems in various domains, such as systems biology, wire routing, and space shuttle control. In this paper, we present an application of ASP to housekeeping robotics. We show how the following problems are addressed using computational methods/tools of ASP: (1) embedding commonsense knowledge automatically extracted from the commonsense knowledge base ConceptNet, into high-level representation, and (2) embedding (continuous) geometric reasoning and temporal reasoning about durations of actions, into (discrete) high-level reasoning. We introduce a planning and monitoring algorithm for safe execution of plans, so that robots can recover from plan failures due to collision with movable objects whose presence and location are not known in advance or due to heavy objects that cannot be lifted alone. Some of the recoveries require collaboration of robots. We illustrate the applicability of ASP on several housekeeping robotics problems, and report on the computational efficiency in terms of CPU time and memory.

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References

  1. Aker E, Erdogan A, Erdem E, Patoglu V (2011) Causal reasoning for planning and coordination of multiple housekeeping robots. In: Proceedings of LPNMR’11

  2. Aker E, Erdogan A, Erdem E, Patoglu V (2011) Housekeeping with multiple autonomous robots: representation, reasoning and execution. In: Proceedings of commonsense’11

  3. Brewka G, Eiter T, Truszczynski M (2011) Answer set programming at a glance. Commun ACM 54(12):92–103

    Article  Google Scholar 

  4. Bylander T (1994) The computational complexity of propositional STRIPS planning. Artif Intell 69(1–2):165–204

    Google Scholar 

  5. Decker K, Lesser V (1992) Generalizing the partial global planning algorithm. Int J Intell Coop Inf Syst 1:319–346

    Google Scholar 

  6. Eén N, Sörensson N (2003) An extensible sat-solver. In: Proceedings of SAT, pp 502–518

  7. Erdem E, Erdem Y, Erdogan H, Oztok U (2011) Finding answers and generating explanations for complex biomedical queries. In: Proceedings of AAAI

  8. Erdem E, Haspalamutgil K, Palaz C, Patoglu V, Uras T (2011) Combining high-level causal reasoning with low-level geometric reasoning and motion planning for robotic manipulation. In: Proceedings of ICRA

  9. Erdem E, Wong MDF (2004) Rectilinear steiner tree construction using answer set programming. In: Proceedings of ICLP, pp 386–399

  10. Ferrein A, Fritz C, Lakemeyer G (2005) Using GOLOG for deliberation and team coordination in robotic soccer. Künstliche Intelligenz 1

  11. Finin TW, Fritzson R, McKay DP, McEntire R (1994) KQML as an agent communication language. In: Proceedings of CIKM, pp 456–463

  12. Gebser M, Guziolowski C, Ivanchev M, Schaub T, Siegel A, Thiele S, Veber P (2010) Repair and prediction (under inconsistency) in large biological networks with answer set programming. In: Proceedings of KR

  13. Gebser M, Kaminski R, Kaufmann B, Ostrowski M, Schaub T, Thiele S (2008) Engineering an incremental ASP solver. In: Proceedings of ICLP, pp 190–205

  14. Gelfond M, Lifschitz V (1991) Classical negation in logic programs and disjunctive databases. New Gener Comput 9:365–385

    Article  Google Scholar 

  15. Giunchiglia E, Lee J, Lifschitz V, McCain N, Turner H (2004) Nonmonotonic causal theories. Artif Intell 153:49–104

    Article  MathSciNet  MATH  Google Scholar 

  16. Lavalle SM (1998) Rapidly-exploring random trees: a new tool for path planning. Tech. rep

  17. Lesser V, Decker K, Carver N, Garvey A, Neimen D, Prassad M, Wagner T (1998) Evolution of the GPGP domain independent coordination framework. Tech. rep., University of Massachusetts

  18. Lifschitz V (2008) What is answer set programming? In: Proceedings of AAAI

  19. Liu H, Singh P (2004) ConceptNet: a practical commonsense reasoning toolkit. BT Technol J 22

  20. Lundh R, Karlsson L, Saffiotti A (2008) Autonomous functional configuration of a network robot system. Robot Auton Syst 56(10):819–830

    Article  Google Scholar 

  21. McCain N, Turner H (1997) Causal theories of action and change. In: Proceedings of AAAI/IAAI, pp 460–465

  22. Nogueira M, Balduccini M, Gelfond M, Watson R, Barry M (2001) An a-prolog decision support system for the space shuttle. In: Proceedings of PADL. Springer, Berlin, pp 169–183

  23. O’Brien PRN (1998) FIPA–towards a standard for software agents. BT Technol J 16(3):51–59

    Article  Google Scholar 

  24. Simons P, Niemelä I, Soininen T (2002) Extending and implementing the stable model semantics. Artif Intell 138:181–234

    Article  MATH  Google Scholar 

  25. Smith RG (1980) The contract net protocol: high-level communication and control in a distributed problem solver. IEEE Trans Comput 29(12):1104–1113

    Google Scholar 

  26. Tari L, Anwar S, Liang S, Hakenberg J, Baral C (2010) Synthesis of pharmacokinetic pathways through knowledge acquisition and automated reasoning. In: Proceedings of PSB, pp 465–476

  27. Vikrey W (1961) Computer speculation, auctions, and competitive sealed tenders. J Finance 16:8–37

    Article  Google Scholar 

  28. de Weerdt MM, Clement B (2009) Introduction to planning in multiagent systems. Multiagent Grid Syst 5:345–355

    Google Scholar 

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Authors and Affiliations

  1. Computer Science and Engineering, Faculty of Engineering and Natural Sciences, Sabancı University, Istanbul, Turkey

    Esra Erdem & Erdi Aker

  2. Mechatronics Engineering, Faculty of Engineering and Natural Sciences, Sabancı University, Istanbul, Turkey

    Volkan Patoglu

Authors
  1. Esra Erdem
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  2. Erdi Aker
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  3. Volkan Patoglu
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Correspondence to Volkan Patoglu.

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Erdem, E., Aker, E. & Patoglu, V. Answer set programming for collaborative housekeeping robotics: representation, reasoning, and execution. Intel Serv Robotics 5, 275–291 (2012). https://doi.org/10.1007/s11370-012-0119-x

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  • DOI: https://doi.org/10.1007/s11370-012-0119-x

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