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A Strategical Path Planner for UGV-UAV Cooperation in Mars Terrains

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Artificial Intelligence XXXV (SGAI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11311))

Abstract

Mars exploration is an ongoing researching topic mainly due to the technological breakthroughs in robotic platforms. Space agencies as NASA, are considering future Mars explorations where multi-robot teams cooperate to maximize the scientific return. In this regard, we present a cooperative team formed by a Unmanned Aerial Vehicle (UAV) and a Unmanned Ground Vehicle (UGV) to autonomously perform a Mars exploration. We develop a strategical path planner to compute a route plan for the UGV-UAV team to reach all the target points of the exploration. The key problems that we have considered in Mars explorations for the UGV-UAV team are: the UAV energy constraints and the UGV functionality constraints. Our strategical path planner models the UGV as a moving charging station which will carry the UAV through secure locations close to the target points locations, and the UAV will visit the target points using the UGV as a recharging station. Our solution has been tested in several scenarios and the results demonstrate that our approach is able to carry out a coordinated plan in a local optimal mission time on a real Mars terrain.

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Acknowledgements

The authors want to thank Dr. David F. Barrero for the fruitful discussions and his help to carry out the experiments. The work is supported by the UAH project 2016/00351/001.

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Authors and Affiliations

  1. Computer Engineering Department, University of Alcalá, 28871, Alcalá de Henares, Spain

    Fernando Ropero, Pablo Muñoz & María D. R-Moreno

Authors
  1. Fernando Ropero
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  2. Pablo Muñoz
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  3. María D. R-Moreno
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Corresponding author

Correspondence to Fernando Ropero .

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Editors and Affiliations

  1. University of Portsmouth, Portsmouth, UK

    Max Bramer

  2. Middlesex University, London, UK

    Miltos Petridis

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Ropero, F., Muñoz, P., R-Moreno, M.D. (2018). A Strategical Path Planner for UGV-UAV Cooperation in Mars Terrains. In: Bramer, M., Petridis, M. (eds) Artificial Intelligence XXXV. SGAI 2018. Lecture Notes in Computer Science(), vol 11311. Springer, Cham. https://doi.org/10.1007/978-3-030-04191-5_8

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  • DOI: https://doi.org/10.1007/978-3-030-04191-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04190-8

  • Online ISBN: 978-3-030-04191-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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