Abstract
The most widely recognized relative directions are left, right, forward and backward. This paper has presented a computational technique for tracking location by learning relative directions between two intelligent agents, where two agents communicate with each other by radio signal and one intelligent agent helps another intelligent agent to find location. This proposed method represents an alternative approach to GSM (Global System for Mobile Communications) for the AI (Artificial Intelligence), where no network may not be available. Our research paper has proposed Relative Direction Based Location Tracking (RDBLT) model for understanding how one intelligent agent assists another intelligent agent to find out the location by learning and identifying relative directions. Moreover, three proficient algorithms have been developed for constructing our proposed model.
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References
Hjelmervika, H., Westerhausena, R., Hirnsteina, M., Spechta, K., Hausmann, M.: The neural correlates of sex differences in left–right confusion. NeuroImage 113, 196–206 (2015)
Götze, J., Boye, J.: “Turn left” versus “walk towards the café”: when relative directions work better than landmarks. In: Bação, F., Santos, M.Y., Painho, M. (eds.) AGILE 2015. LNGC, pp. 253–267. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-16787-9_15
Albert, W.S., Rensink, A., Beusmans, J.M.: Learning relative directions between landmarks in a desktop virtual environmen. Spat. Cogn. Comput. 1, 131–144 (1999)
Weng, C.E., Lai, T.W.: An energy-efficient routing algorithm based on relative identification and direction for wireless sensor networks. Wirel. Pers. Commun. 69, 253–268 (2013)
Kabir, S.R., Allayear, S.M., Alam, M.M., Munna, M.T.A.: A computational technique for intelligent computers to learn and identify the human’s relative directions. In: International Conference on Intelligent Sustainable Systems, pp. 1036–1039. IEEE Xplore, India (2017)
Lurz, F., Mueller, S., Lindner, S., Linz, S., Gardill, M., Weigel, R., Koelpin, A.: Smart communication and relative localization system for firefighters and rescuers. In: 2017 IEEE MTT-S International Microwave Symposium (IMS), pp. 1421–1424. IEEE Xplore, USA (2017)
Lowrance, C.J., Lauf, A.P.: Direction of arrival estimation for robots using radio signal strength and mobility. In: 2016 13th Workshop on Positioning, Navigation and Communications (WPNC). IEEE Press (2016)
Kolster, A.F., Dunmore, F.W.: The Radio Direction Finder and Its Application to Navigation, Washington (1921)
Mahmood, A., Wallace, J.W., Jensen, M.A.: Radio frequency UAV attitude estimation using direction of arrival and polarization. In: 11th European Conference on Antennas and Propagation, pp. 1857–1859. IEEE Press, France (2017)
Kabir, S.R.: Computation of multi-agent based relative direction learning specification. B.Sc. thesis, Daffodil International University, Bangladesh (2017)
Mossakowski, T., Moratz, R.: Qualitative reasoning about relative direction of oriented points. Artif. Intell. 180–181, 34–45 (2012)
Moratz, R.: Representing relative direction as a binary relation of oriented points. In: 17th European Conference on Artificial Intelligence, pp. 407–411. IOS Press, Netherlands (2006)
Hahn, S., Bethge, J., Döllner, J.: Relative direction change - a topology-based metric for layout stability in treemaps. In: 12th International Conference on Information Visualization Theory and Applications, pp. 88–95. Portugal (2017)
Lee, J.H., Renz, J., Wolter, D.: StarVars—effective reasoning about relative directions. In: Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 2013), pp. 976–982. AAAI Press, California (2013)
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Kabir, S.R., Alam, M.M., Allayear, S.M., Munna, M.T.A., Hossain, S.S., Rahman, S.S.M.M. (2018). Relative Direction: Location Path Providing Method for Allied Intelligent Agent. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 905. Springer, Singapore. https://doi.org/10.1007/978-981-13-1810-8_38
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DOI: https://doi.org/10.1007/978-981-13-1810-8_38
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