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A Hybrid Visual-Model Based Robot Control Strategy for Micro Ground Robots

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From Animals to Animats 15 (SAB 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10994))

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Abstract

This paper proposed a hybrid vision-based robot control strategy for micro ground robots by mediating two vision models from mixed categories: a bio-inspired collision avoidance model and a segmentation based target following model. The implemented model coordination strategy is described as a probabilistic model using finite state machine (FSM) that allows the robot to switch behaviours adapting to the acquired visual information. Experiments demonstrated the stability and convergence of the embedded hybrid system by real robots, including the studying of collective behaviour by a swarm of such robots with environment mediation. This research enables micro robots to run visual models with more complexity. Moreover, it showed the possibility to realize aggregation behaviour on micro robots by utilizing vision as the only sensing modality from non-omnidirectional cameras.

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Acknowledgement

This work is supported by EU-FP7-IRSES project HAZCEPT(318907) and Horizon2020 project STEP2DYNA.

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Authors and Affiliations

  1. University of Lincoln, Lincoln, UK

    Cheng Hu, Qinbing Fu, Tian Liu & Shigang Yue

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

Correspondence to Cheng Hu .

Editor information

Editors and Affiliations

  1. University of Southern Denmark, Odense, Denmark

    Poramate Manoonpong

  2. University of Southern Denmark, Odense, Denmark

    Jørgen Christian Larsen

  3. University of Southern Denmark, Odense, Denmark

    Xiaofeng Xiong

  4. University of Southern Denmark, Odense, Denmark

    John Hallam

  5. Frankfurt Institute for Advanced Studies, Frankfurt/Main, Germany

    Jochen Triesch

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Hu, C., Fu, Q., Liu, T., Yue, S. (2018). A Hybrid Visual-Model Based Robot Control Strategy for Micro Ground Robots. In: Manoonpong, P., Larsen, J., Xiong, X., Hallam, J., Triesch, J. (eds) From Animals to Animats 15. SAB 2018. Lecture Notes in Computer Science(), vol 10994. Springer, Cham. https://doi.org/10.1007/978-3-319-97628-0_14

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  • DOI: https://doi.org/10.1007/978-3-319-97628-0_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97627-3

  • Online ISBN: 978-3-319-97628-0

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