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Convolutional Neuronal Networks Based Monocular Object Detection and Depth Perception for Micro UAVs

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Intelligence Science and Big Data Engineering (IScIDE 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11266))

Abstract

In this work, we present the development of a system for the detection and depth estimation of objects in real time using the on-board camera in a micro-UAV through convolutional neuronal networks. Traditionally for the detection of obstacles shows the use of SLAM visual systems. However, to solve this problem, this level of complexity is not necessary, saving resources and execution time. The training with convolutional neural networks using stereo images for the depth estimation and in the same way training the detection of common observable objects can obtain an accurate detection of obstacles in a real time.

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Acknowledgement

This work is part of the project Perception and localization system for autonomous navigation of rotor micro aerial vehicle in gps-denied environments, VisualNavDrone, 2016-PIC-024, from the Universidad de las Fuerzas Armadas ESPE, directed by Dr. Wilbert G. Aguilar.

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Authors and Affiliations

  1. CICTE Research Center, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Wilbert G. Aguilar, Fernando J. Quisaguano, Guillermo A. Rodríguez, Leandro G. Alvarez, Alex Limaico & David S. Sandoval

  2. FIS Faculty, Escuela Politécnica Nacional, Quito, Ecuador

    Wilbert G. Aguilar

  3. GREC Research Group, Universitat Politècnica de Catalunya, Barcelona, Spain

    Wilbert G. Aguilar

Authors
  1. Wilbert G. Aguilar
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  2. Fernando J. Quisaguano
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  3. Guillermo A. Rodríguez
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  4. Leandro G. Alvarez
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  5. Alex Limaico
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  6. David S. Sandoval
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Corresponding author

Correspondence to Wilbert G. Aguilar .

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Editors and Affiliations

  1. Peking University, Beijing, China

    Yuxin Peng

  2. Shanghai Jiao Tong University, Shanghai, China

    Kai Yu

  3. Tsinghua University, Beijing, China

    Jiwen Lu

  4. Central China Normal University, Wuhan, China

    Xingpeng Jiang

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Aguilar, W.G., Quisaguano, F.J., Rodríguez, G.A., Alvarez, L.G., Limaico, A., Sandoval, D.S. (2018). Convolutional Neuronal Networks Based Monocular Object Detection and Depth Perception for Micro UAVs. In: Peng, Y., Yu, K., Lu, J., Jiang, X. (eds) Intelligence Science and Big Data Engineering. IScIDE 2018. Lecture Notes in Computer Science(), vol 11266. Springer, Cham. https://doi.org/10.1007/978-3-030-02698-1_35

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  • DOI: https://doi.org/10.1007/978-3-030-02698-1_35

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