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Convolutional Neural Network-Based Local Obstacle Avoidance for a Mobile Robot

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Automation 2021: Recent Achievements in Automation, Robotics and Measurement Techniques (AUTOMATION 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1390))

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Abstract

This paper presents collision avoidance and local motion planning modules for a mobile robot equipped with a depth camera. In this paper, we identify some limitations of the existing neural controller, and then we propose the extensions which improve the behavior of the robot. We show that the knowledge about control history is crucial to efficiently avoid collisions with the obstacles if the robot is equipped with a narrow field of view camera. We propose the architecture which utilizes CNN-based neural modules to plan the local motion of the robot. Finally, we provide the results of the experimental verification on the real robot.

This work was supported by the National Centre for Research and Development (NBR) through project LIDER/33/0176/L-8/16/NCBR/2017. We would like to thank Lei Tai, Shaohua Li and Ming Liu for sharing raw data from their experiments.

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Notes

  1. 1.

    short video from experiments is available at https://youtu.be/6ssP9L52_WQ.

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Authors and Affiliations

  1. Institute of Robotics and Machine Intelligence, Poznan University of Technology, ul. Piotrowo 3A, 60-965, Poznan, Poland

    Milena Molska & Dominik Belter

Authors
  1. Milena Molska
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  2. Dominik Belter
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Corresponding author

Correspondence to Dominik Belter .

Editor information

Editors and Affiliations

  1. ŁUKASIEWICZ Research Network, Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Roman Szewczyk

  2. ŁUKASIEWICZ Research Network, Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Cezary Zieliński

  3. ŁUKASIEWICZ Research Network, Industrial Research Institute for Automation and Measurements PIAP, Warsaw, Poland

    Małgorzata Kaliczyńska

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Molska, M., Belter, D. (2021). Convolutional Neural Network-Based Local Obstacle Avoidance for a Mobile Robot. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2021: Recent Achievements in Automation, Robotics and Measurement Techniques. AUTOMATION 2021. Advances in Intelligent Systems and Computing, vol 1390. Springer, Cham. https://doi.org/10.1007/978-3-030-74893-7_25

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