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Colias IV: The Affordable Micro Robot Platform with Bio-inspired Vision

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Towards Autonomous Robotic Systems (TAROS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10965))

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Abstract

Vision is one of the most important sensing modalities for robots and has been realized on mostly large platforms. However for micro robots which are commonly utilized in swarm robotic studies, the visual ability is seldom applied or with reduced functions/resolution, due to the high demanding on the computation power. This research has proposed the low-cost micro ground robot Colias IV, which is particularly designed to meet the requirements to allow embedded vision based tasks on-board, such as bio-inspired collision detection neural networks. Numerous of successful approaches have demonstrated that the proposed micro robot Colias IV to be a feasible platform for introducing visual based algorithms into swarm robotics.

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Acknowledgement

This work was supported by the EU FP7 project HAZCEPT (318907) and Horizon 2020 project STEP2DYNA (691154).

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Authors and Affiliations

  1. Lincoln Centre for Autonomous Systems Research, University of Lincoln, Lincoln, UK

    Cheng Hu, Qinbing Fu & Shigang Yue

Authors
  1. Cheng Hu
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  2. Qinbing Fu
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  3. Shigang Yue
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Corresponding author

Correspondence to Cheng Hu .

Editor information

Editors and Affiliations

  1. University of the West of England, Bristol, United Kingdom

    Manuel Giuliani

  2. University of Bath, Bath, United Kingdom

    Tareq Assaf

  3. University of Bristol, Bristol, United Kingdom

    Maria Elena Giannaccini

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Hu, C., Fu, Q., Yue, S. (2018). Colias IV: The Affordable Micro Robot Platform with Bio-inspired Vision. In: Giuliani, M., Assaf, T., Giannaccini, M. (eds) Towards Autonomous Robotic Systems. TAROS 2018. Lecture Notes in Computer Science(), vol 10965. Springer, Cham. https://doi.org/10.1007/978-3-319-96728-8_17

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  • DOI: https://doi.org/10.1007/978-3-319-96728-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96727-1

  • Online ISBN: 978-3-319-96728-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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