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Advancing multi-vehicle deployments in oceanographic field experiments

Abstract

Our research concerns the coordination and control of robotic vehicles for upper water-column oceanographic observations. In such an environment, operating multiple vehicles to observe dynamic oceanographic phenomena, such as ocean processes and marine life, from fronts to cetaceans, has required that we design, implement and operate software, methods and processes which can support opportunistic needs in real-world settings with substantial constraints. In this work, an approach for coordinated measurements using such platforms, which relate directly to task outcomes, is presented. We show the use and operational value of a new Artificial Intelligence based mixed-initiative system for handling multiple platforms along with the networked infrastructure support needed to conduct such operations in the open sea. We articulate the need and use of a range of middleware architectures, critical for such deployments and ground this in the context of a field experiment in open waters of the mid-Atlantic in the summer of 2015.

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Notes

  1. 1.

    http://rep15.lsts.pt/.

  2. 2.

    http://github.com/LSTS.

  3. 3.

    https://github.com/google/guava.

  4. 4.

    https://github.com/fredpy/trex2-agent/.

  5. 5.

    https://github.com/nasa/europa.

  6. 6.

    The acceptable distance to the desired end point.

  7. 7.

    There can be additional flaw types depending on the solver being used; but these are the minimum needed to converge to a solution.

  8. 8.

    Both the launch/recovery operation and charging times where approximate, yet reasonable estimates.

  9. 9.

    Note: acoustic communication was only used for vehicle telemetry.

  10. 10.

    http://goo.gl/hEVmFU.

  11. 11.

    http://www.rock7mobile.com/products-iridium-sbd.

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Acknowledgements

Johansen was supported in part by the Research Council of Norway through the Centers of Excellence funding scheme, grant number 223254 – NTNU AMOS, and by grant number 235348. Rajan and Py were supported by the US Office of Naval Research, ONR Grant # N00014-14-1-0536. Silva was supported by FEDER and COMPETE funds and by FCT grant # IF/00943/2013. Silva was also supported by FRCT from the Government of the Açores. Authors are grateful to the Cetacean Ecology Research Group including Pablo Chellavard Navarro, Rui Prieto, Cláudia Oliveira, Marta Tobena, and skipper Renato Bettencourt, and to NTNU’s UAV team, including Lars Semb, Krzysztof Cisek, Frederik Leira and João Fortuna. This work was partially supported by the SUNRISE - “Sensing, monitoring and actuating on the UNderwater world through a federated Research InfraStructure Extending the Future Internet”, project #611449, funded by the European Union’s Seventh Framework Programme for Research and Technological Development - Large scale integrating project (IP). We are grateful to the captain and crew of NRP Gago Coutinho. Finally, we are grateful to the entire ls team that participated in the rp exercise in the Açores.

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Correspondence to António Sérgio Ferreira.

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Ferreira, A.S., Costa, M., Py, F. et al. Advancing multi-vehicle deployments in oceanographic field experiments. Auton Robot 43, 1555–1574 (2019). https://doi.org/10.1007/s10514-018-9810-x

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Keywords

  • Mixed-initiative control
  • Marine robotics
  • Control
  • Artificial Intelligence
  • Ocean science
  • Operational oceanography
  • Upper water-column biology