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International Conference on Brain Informatics

BIH 2016: Brain Informatics and Health pp 355–364Cite as

Brain-Inspired Obstacle Detection Based on the Biological Visual Pathway

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9919))

Abstract

Obstacle detection is crucial for intelligent systems (e.g. robots, unmanned ariel vehicle) that interact with the real world. This paper proposes a brain-inspired rasterization algorithm for obstacle detection. Rasterization algorithm is inspired by the information processing mechanism of the biological brain (including arthropod brain and human brain). Obstacle detection relies on feed forward and feed backward information processing mechanism. Receptive fields in every level of abstraction transmit different sizes of image regions to higher levels. Feedback is related to modulating attention about the position and size of target receptive field. Inspired by the circuit in human vision system, this paper provides a computational model for obstacle detection. Good performance on the experiments supports the proposed theoretical model. The major contribution of the proposed brain-inspired rasterization algorithm is that it can detect obstacle in any size from any direction without any preprocessing.

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Acknowledgments

This study was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB02060007), and Beijing Municipal Commission of Science and Technology (Z151100000915070, Z161100000216124).

Author information

Authors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Yi Zeng, Feifei Zhao, Guixiang Wang, Lingyu Zhang & Bo Xu

  2. Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China

    Yi Zeng, Feifei Zhao, Guixiang Wang, Lingyu Zhang & Bo Xu

Authors
  1. Yi Zeng
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  2. Feifei Zhao
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  3. Guixiang Wang
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  4. Lingyu Zhang
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  5. Bo Xu
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Corresponding author

Correspondence to Yi Zeng .

Editor information

Editors and Affiliations

  1. George Mason University, Fairfax, Virginia, USA

    Giorgio A. Ascoli

  2. Department of Modeling, Analysis and Theory, Allen Institute for Brain Science, Seattle, Washington, USA

    Michael Hawrylycz

  3. University of Nebraska Omaha, Omaha, Nebraska, USA

    Hesham Ali

  4. Information Science and Technology, University of Nebraska Omaha, Omaha, Nebraska, USA

    Deepak Khazanchi

  5. College of Information Sciences and Technology, University of Nebraska Omaha, Omaha, Nebraska, USA

    Yong Shi

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© 2016 Springer International Publishing AG

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Zeng, Y., Zhao, F., Wang, G., Zhang, L., Xu, B. (2016). Brain-Inspired Obstacle Detection Based on the Biological Visual Pathway. In: Ascoli, G., Hawrylycz, M., Ali, H., Khazanchi, D., Shi, Y. (eds) Brain Informatics and Health. BIH 2016. Lecture Notes in Computer Science(), vol 9919. Springer, Cham. https://doi.org/10.1007/978-3-319-47103-7_35

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  • DOI: https://doi.org/10.1007/978-3-319-47103-7_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47102-0

  • Online ISBN: 978-3-319-47103-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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