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Hybrid Evolutionary Approach to Multi-objective Mission Planning for Group of Underwater Robots

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Mathematical Modeling of Technological Processes (CITech 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 549))

Abstract

We propose a hybrid approach, based on the combined use of genetic algorithms, methods and heuristics of local search, and ant colony optimization to solve the dynamic routing problem for a group of underwater robots. Group’s objective involves visiting a certain set of control points (for the purpose of sampling, taking measurements, photos and videos) according to their priority and under given restrictions. The dynamic routing problem here is to find (planning) and adjust (replanning) feasible group routes for robots, ensuring as far as possible the maximum efficiency of the group work.

The reported study was partly funded by RFBR according to the research projects No. 14-07-00740-a, 14-07-31192-mol-a.

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References

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Author information

Authors and Affiliations

  1. Matrosov Institute for System Dynamics and Control Theory, Lermontov Str., 134, 664033, Irkutsk, Russia

    Maksim Kenzin, Igor Bychkov & Nikolai Maksimkin

Authors
  1. Maksim Kenzin
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  2. Igor Bychkov
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  3. Nikolai Maksimkin
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Corresponding author

Correspondence to Maksim Kenzin .

Editor information

Editors and Affiliations

  1. Al-Farabi Kazakh National University, Almaty, Kazakhstan

    Nargozy Danaev

  2. Novosibirsk, Russia

    Yurii Shokin

  3. National University, Almaty, Kazakhstan

    Akhmed-Zaki Darkhan

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© 2015 Springer International Publishing Switzerland

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Kenzin, M., Bychkov, I., Maksimkin, N. (2015). Hybrid Evolutionary Approach to Multi-objective Mission Planning for Group of Underwater Robots. In: Danaev, N., Shokin, Y., Darkhan, AZ. (eds) Mathematical Modeling of Technological Processes. CITech 2015. Communications in Computer and Information Science, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-25058-8_8

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  • DOI: https://doi.org/10.1007/978-3-319-25058-8_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25057-1

  • Online ISBN: 978-3-319-25058-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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