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Comparison Between Filtering Estimation with Evidence and Prediction Filtering Without Evidence to Predict a Robot Localization States

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2021 (AISI 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 100))

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Abstract

Today, robotics has experienced a very interesting technological revolution, given the diversity of applications that use autonomous robots in several areas, such as mining exploration. However, prediction with great precision of robot localizations remains a research subject that is always in continuous improvement. In this context, our study consists of a robot, which can move within an area of 15 tiles. It is equipped with a sensing system, which detects obstacles in four directions: north, south, east, and west. The sensors have an error rate of e = 25%. The first step of this study is to model our system by Hidden Markov Model to predict the Robot localization states using the comparison between the Filtering estimation method with Evidence and the Prediction Filtering without Evidence.

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Acknowledgments

In the term of this paper, we thank the Laboratory of Mechanic, Mechatronics and Control (L2MC) of the ENSAM MEKNES. We do not forget both our colleagues and experts for the information source. In addition, we thank the steering committee of the International Conference on Advanced Intelligent Systems and Informatics (AISI 2021) for allowing us to communicate our works and results.

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Authors and Affiliations

  1. Laboratory of Mechanics, Mechatronics and Control (L2MC), Moulay Ismail University, ENSAM Meknes, Marjane 2, Al-Mansour Road Agouray, PO Box 15290, 50500, Meknes, Morocco

    Jaouad Boudnaya, Marouan Cherrat, Ilham Gharib & Abdelhak Mkhida

Authors
  1. Jaouad Boudnaya
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  2. Marouan Cherrat
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  3. Ilham Gharib
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  4. Abdelhak Mkhida
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Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Faculty of Computers and Artificial Intelligence, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava, Ostrava-Poruba, Moravskoslezsky, Czech Republic

    Václav Snášel

  3. Fujian University of Technology, Shulin District, New Taipei, Taiwan

    Kuo-Chi Chang

  4. Faculty of Science, Helwan University, Cairo, Egypt

    Ashraf Darwish

  5. University of Salford, Manchester, UK

    Tarek Gaber

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Boudnaya, J., Cherrat, M., Gharib, I., Mkhida, A. (2022). Comparison Between Filtering Estimation with Evidence and Prediction Filtering Without Evidence to Predict a Robot Localization States. In: Hassanien, A.E., Snášel, V., Chang, KC., Darwish, A., Gaber, T. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2021. AISI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 100. Springer, Cham. https://doi.org/10.1007/978-3-030-89701-7_13

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