Skip to main content

ARGO: An Extended Jason Architecture that Facilitates Embedded Robotic Agents Programming

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10093))

Abstract

This paper presents ARGO, a customized Jason architecture for programming embedded robotic agents using the Javino middleware and perception filters. Jason is a well known agent-oriented programming language that relies on the Belief-Desire-Intention model and implements an AgentSpeak interpreter in Java. Javino is a middleware that enables automated design of embedded agents using Jason and it is aimed to be used in the robotics domain. However, when the number of perceptions increases, it may occur a bottleneck in the agent’s reasoning cycle since an event is generated for each single perception processed. A possible solution to this problem is to apply perception filters, that reduce the processing cost. Consequently, it is expected that the agent may deliberate within a specific time limit. In order to evaluate ARGO’s performance, we present some experiments using a ground vehicle platform in a real-time collision scenario. We show that in certain cases the use of perception filters is able to prevent collisions effectively.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    Download available at http://argo-for-jason.sourceforge.net.

  2. 2.

    The speed is about 10 cm/s and it is not used in the experiments since it is constant.

References

  1. Barros, R.S., Heringer, V.H., Lazarin, N.M., Pantoja, C.E., Moraes, L.M.: An agent-oriented ground vehicle’s automation using Jason framework. In: 6th International Conference on Agents and Artificial Intelligence, pp. 261–266 (2014)

    Google Scholar 

  2. Bordini, R.H., Hübner, J.F., Wooldridge, M.: Programming Multi-Agent Systems in AgentSpeak using Jason. John Wiley & Sons Ltd., Chichester (2007)

    Book  MATH  Google Scholar 

  3. Bratman, M.E.: Intention, Plans and Practical Reasoning. Cambridge Press, Cambridge (1987)

    Google Scholar 

  4. Calce, A., Forooshani, P.M., Speers, A., Watters, K., Young, T., Jenkin, M.R.: Autonomous aquatic agents. In: ICAART (1), pp. 372–375 (2013)

    Google Scholar 

  5. Chen, S.Y.: Kalman filter for robot vision: a survey. IEEE Trans. Industr. Electron. 59(11), 4409–4420 (2012)

    Article  Google Scholar 

  6. Clark, K., Robinson, P.: Robotic agent programming in TeleoR. In: 2015 IEEE International Conference on Robotics and Automation, pp. 5040–5047 (2015)

    Google Scholar 

  7. Dastani, M., de Boer, F., Dignum, F., Van Der Hoek, W., Kroese, M., Meyer, J.J., et al.: Programming the deliberation cycle of cognitive robots. In: Proceedings of the 3rd International Cognitive Robotics Workshop (2002)

    Google Scholar 

  8. Guinelli, J.V., Junger, D., Pantoja, C.E.: An analysis of Javino middleware for robotic platforms using Jason and JADE frameworks. In: 10th Software Agents, Environments and Applications School (2016)

    Google Scholar 

  9. Hama, M.T.: Uma plataforma orientada a agentes para o desenvolvimento de software em veículos aéreos não-tripulados. Master’s thesis, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil (2012)

    Google Scholar 

  10. Hindriks, K.V.: Programming rational agents in GOAL. In: Seghrouchni, A., Dix, J., Dastani, M., Bordini, H.R. (eds.) Multi-Agent Programming: Languages, Tools and Applications, pp. 119–157. Springer, Boston (2009)

    Chapter  Google Scholar 

  11. Hindriks, K.V., De Boer, F.S., Van der Hoek, W., Meyer, J.J.C.: Agent programming in 3APL. Auton. Agent. Multi-Agent Syst. 2(4), 357–401 (1999)

    Article  Google Scholar 

  12. Jain, R.: Art of Computer Systems Performance Analysis: Techniques For Experimental Design Measurements Simulation and Modeling. Wiley (2015)

    Google Scholar 

  13. Kuiper, D.M., Wenkstern, R.Z.: Agent vision in multi-agent based simulation systems. Auton. Agent. Multi-Agent Syst. 29(2), 161–191 (2015)

    Article  Google Scholar 

  14. Lazarin, N.M., Pantoja, C.E.: A robotic-agent platform for embedding software agents using raspberry pi and arduino boards. In: 9th Software Agents, Environments and Applications School (2015)

    Google Scholar 

  15. Morais, M., Meneguzzi, F., Bordini, R., Amory, A.: Distributed fault diagnosis for multiple mobile robots using an agent programming language. In: 2015 International Conference on Advanced Robotics (ICAR), pp. 395–400 (2015)

    Google Scholar 

  16. Mordenti, A., Ricci, A., Santi, D.I.A.: Programming robots with an agent-oriented bdi-based control architecture: Explorations using the jaca and webots platforms. Bologna, Italy, Technical report (2012)

    Google Scholar 

  17. Rao, A.S.: AgentSpeak(L): BDI agents speak out in a logical computable language. In: Velde, W., Perram, J.W. (eds.) MAAMAW 1996. LNCS, vol. 1038, pp. 42–55. Springer, Heidelberg (1996). doi:10.1007/BFb0031845

    Chapter  Google Scholar 

  18. Ricci, A., Piunti, M., Viroli, M., Omicini, A.: Environment programming in CArtAgO. In: Seghrouchni, A., Dix, J., Dastani, M., Bordini, H.R. (eds.) Multi-Agent Programming: Languages, Tools and Applications, pp. 259–288. Springer, Boston (2009)

    Chapter  Google Scholar 

  19. Santos, F.R., Hübner, J.F., Becker, L.B.: Concepção e análise de um modelo de agente BDI voltado para o planejamento de rota em um VANT. In: 9th Software Agents, Environments and Applications School (2015)

    Google Scholar 

  20. Stabile Jr., M.F., Sichman, J.S.: Evaluating perception filters in BDI Jason agents. In: 4th Brazilian Conference on Intelligent Systems (BRACIS) (2015)

    Google Scholar 

  21. Wei, C., Hindriks, K.V.: An agent-based cognitive robot architecture. In: Dastani, M., Hübner, J.F., Logan, B. (eds.) ProMAS 2012. LNCS (LNAI), vol. 7837, pp. 54–71. Springer, Heidelberg (2013). doi:10.1007/978-3-642-38700-5_4

    Chapter  Google Scholar 

  22. Wooldridge, M.J.: Reasoning About Rational Agents. MIT Press, Cambridge (2000)

    MATH  Google Scholar 

Download references

Acknowledgments

Márcio F. Stabile Jr. is financed by CNPq. Carlos Pantoja is financed by CAPES. Jaime Simão Sichman is partially financed by CNPq, proc.303950/2013-7.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Carlos Eduardo Pantoja .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Pantoja, C.E., Stabile, M.F., Lazarin, N.M., Sichman, J.S. (2016). ARGO: An Extended Jason Architecture that Facilitates Embedded Robotic Agents Programming. In: Baldoni, M., Müller, J., Nunes, I., Zalila-Wenkstern, R. (eds) Engineering Multi-Agent Systems. EMAS 2016. Lecture Notes in Computer Science(), vol 10093. Springer, Cham. https://doi.org/10.1007/978-3-319-50983-9_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-50983-9_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50982-2

  • Online ISBN: 978-3-319-50983-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics