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Obstacle Avoidance by a Mobile Platform Using an Ultrasound Sensor

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Computational Collective Intelligence (ICCCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10449))

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Abstract

The problems of obstacle avoidance occur in many areas for autonomous vehicles. In automotive field, Advanced Driver Assistance Systems modules equipped with sensor fusion are used to resolve these problems. In the case of small mobile platforms, electronic sensors such as ultrasound, gyroscopes, magnetometers and encoders are commonly used. The data obtained from these sensors is measured and processed, which permits the development of automatic obstacle avoidance functions for mobile platforms. The information from these sensors is sufficient to detect obstacles, determine the distance to obstacles and prepare actions to avoid the obstacles. This paper presents the results of research on two obstacle avoidance algorithms that were prepared for small mobile platforms that take advantage of an ultrasonic sensor. The presented solutions are based on calculating the weights of the possible directions for obstacle avoidance and the geometric analysis of an obstacle.

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Acknowledgements

This work was supported by the European Union through the FP7-PEOPLE-2013-IAPP AutoUniMo project “Automotive Production Engineering Unified Perspective based on Data Mining Methods and Virtual Factory Model” (Grant Agreement No: 612207) and research work financed from funds for science for years: 2016–2017 allocated to an international co-financed project.

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Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Adam Ziebinski, Rafal Cupek & Marek Nalepa

Authors
  1. Adam Ziebinski
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  2. Rafal Cupek
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  3. Marek Nalepa
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Corresponding author

Correspondence to Adam Ziebinski .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  3. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Piotr Jędrzejowicz

  4. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. Department of Information Systems, University of Münster, Münster, Germany

    Gottfried Vossen

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Ziebinski, A., Cupek, R., Nalepa, M. (2017). Obstacle Avoidance by a Mobile Platform Using an Ultrasound Sensor. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10449. Springer, Cham. https://doi.org/10.1007/978-3-319-67077-5_23

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  • DOI: https://doi.org/10.1007/978-3-319-67077-5_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67076-8

  • Online ISBN: 978-3-319-67077-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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