Abstract
Fuzzy Cognitive Maps (FCM) started in the last decade to penetrate to areas as decision-making and control systems including robotics, which is characterized by its distributiveness, need for parallelism and heterogeneity of used means. This chapter deals with specification of needs for a robot control system and divides defined tasks into three basic decision levels dependent on their specification of use as well as applied means. Concretely, examples of several FCMs applications from the low and middle decision levels are described, mainly in the area of navigation, movement stabilization, action selection and path cost evaluation. Finally, some outlooks for future development of FCMs are outlined.
Keywords
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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Beeson, P., Modayil, J., Kuipers, B.: Factoring the mapping problem: mobile robot map-building in the hybrid spatial semantic hierarchy. Int. J. Robot. Res. 29(4), 428–459 (2010)
Blažič, S., Škrjanc, I., Matko, D.: Globally stable direct fuzzy model reference adaptive control. Fuzzy Sets Syst. 139(1), 3–33 (2003)
Golmohammadi, S.K., Azadeh, A., Gharehgozli, A.: Action selection in robots based on learning fuzzy cognitive map, pp. 731–736. In: Proceeding of IEEE International Conference on Industrial Informatics, Singapore (2006)
Kannappan, A., Tamilarasi, A., Papageorgiou, E.: Analyzing the performance of fuzzy cognitive maps with non-linear hebbian learning algorithm in predicting autistic disorder. Expert Syst. Appl. 38(3), 1282–1292 (2011)
Kosko, B.: Fuzzy cognitive maps. Int. J. Man Mach. Stud. 24(1), 65–75 (1986)
LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge. http://planning.cs.uiuc.edu/ (2006)
Matarić, M.J.: Learning in behavior-based multi-robot systems: policies, models, and other agents. Cogn. Syst. Res. 2(1), 81–93 (2001)
Medgyes, K., Johanyák, Z.C.: Survey on routing algorithms. In: Proceeding of 3rd International Scientific and Expert Conference (TEAM 2011), Trnava, Slovakia, pp. 312–315 (2012)
Mendonça, M., de Arruda, L., Neves, F.: Autonomous navigation system using event driven-fuzzy cognitive maps. Appl. Intel. 37, 175–188 (2012)
Motlagh, O.: An FCM-based design for balancing of legged robots. J. Artif.Intel. 4(4), 295–299 (2011)
Motlagh, O., Tang, S.H., Ismail, N., Ramli, A.R.: An expert fuzzy cognitive map for reactive navigation of mobile robots. Fuzzy Sets Syst. 201, 105–121 (2012)
Papageorgiou, E.: Learning algorithms for fuzzy cognitive maps:a review study. Syst. Man Cybern. Part C Appl. Rev. IEEE Trans. 42(2), 150–163 (2012)
Papageorgiou, E.I., Froelich, W.: Multi-step prediction of pulmonary infection with the use of evolutionary fuzzy cognitive maps. Neurocomputing 92, 28–35 (2012)
Papageorgiou, E.I., Iakovidis, D.K.: Intuitionistic fuzzy cognitive maps. IEEE Trans. Fuzzy Syst. 21(2), 342–354 (2013)
Papageorgiou, E.I., Kannappan, A.: Fuzzy cognitive map ensemble learning paradigm to solve classification problems: application to autism identification. Appl. Soft Comput. 12(12), 3798–3809 (2012)
Papageorgiou, E.I., Salmeron, J.L.: Learning fuzzy grey cognitive maps using nonlinear hebbian-based approach. Int. J. Approx. Reason. 53(1), 54–65 (2012)
Papageorgiou, E.I., Salmeron, J.L.: A review of fuzzy cognitive maps research during the last decade. IEEE Trans. Fuzzy Syst. 21(1), 66–79 (2013)
Parenthoën, M., Reignier, P., Tisseau, J.: Put fuzzy cognitive maps to work in virtual worlds. In: Proceeding of the 10th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), vol. 1, pp. 252–255, Melbourne, Australia (2001)
Pozna, C., Troester, F., Precup, R.E., Tar, J.K., Preitl, S.: On the design of an obstacle avoiding trajectory: method and simulation. Math. Comput. Simul. 79(7), 2211–2226 (2009)
Precup, R.E., Hellendoorn, H.: A survey on industrial applications of fuzzy control. Comput. Ind. 62(3), 213–226 (2011)
Stach, W., Kurgan, L., Pedrycz, W., Reformat, M.: Genetic learning of fuzzy cognitive maps. Fuzzy Sets Syst. 153(3), 371–401 (2005)
Vaščák, J.: Fuzzy cognitive maps in path planning. Acta Tech. Jaurinensis 1(3), 467–479 (2008)
Vaščák, J.: Decision-making systems in mobile robotics. In: Mls, K. (ed.) Autonomous Decision Systems Handbook, pp. 56–88. BEN, Prague (2011)
Vaščák, J., Hirota, K.: Integrated decision-making system for robot soccer. J. Adv. Comput. Intel. Intel. Inf. 15(2), 156–163 (2011)
Vaščák, J., Madarász, L.: Adaptation of fuzzy cognitive maps—a comparison study. Acta Polytech. Hung. 7(3), 109–122 (2010)
Vaščák, J., Paľa ,M.: Adaptation of fuzzy cognitive maps for navigation purposes by migration algorithms. Int. J. Artif. Intel. 8(S12), 20–37 (2012)
Zelinka, I.: Artificial Intelligence in Problems of Global Optimization. BEN, Prague (2002)
Acknowledgments
Research supported by the National Research and Development Project Grant 1/0667/12 “Incremental Learning Methods for Intelligent Systems” 2012–2015 and by the “Center of Competence of knowledge technologies for product system innovation in industry and service” with ITMS project number: 26220220155 for years 20012–2015.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
1 Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary material 1 (AVI 25,594 KB)
Supplementary material 1 (AVI 28,004 KB)
Supplementary material 1 (AVI 28,863 KB)
Supplementary material 1 (AVI 11,397 KB)
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Vaščák, J., Reyes, N.H. (2014). Use and Perspectives of Fuzzy Cognitive Maps in Robotics. In: Papageorgiou, E. (eds) Fuzzy Cognitive Maps for Applied Sciences and Engineering. Intelligent Systems Reference Library, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39739-4_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-39739-4_15
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39738-7
Online ISBN: 978-3-642-39739-4
eBook Packages: EngineeringEngineering (R0)