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Autonomous Robots

, Volume 40, Issue 7, pp 1279–1306 | Cite as

Toward persistent autonomous intervention in a subsea panel

  • Narcís PalomerasEmail author
  • Arnau Carrera
  • Natàlia Hurtós
  • George C. Karras
  • Charalampos P. Bechlioulis
  • Michael Cashmore
  • Daniele Magazzeni
  • Derek Long
  • Maria Fox
  • Kostas J. Kyriakopoulos
  • Petar Kormushev
  • Joaquim Salvi
  • Marc Carreras
Article

Abstract

Intervention autonomous underwater vehicles (I-AUVs) have the potential to open new avenues for the maintenance and monitoring of offshore subsea facilities in a cost-effective way. However, this requires challenging intervention operations to be carried out persistently, thus minimizing human supervision and ensuring a reliable vehicle behaviour under unexpected perturbances and failures. This paper describes a system to perform autonomous intervention—in particular valve-turning—using the concept of persistent autonomy. To achieve this goal, we build a framework that integrates different disciplines, involving mechatronics, localization, control, machine learning and planning techniques, bearing in mind robustness in the implementation of all of them. We present experiments in a water tank, conducted with Girona 500 I-AUV in the context of a multiple intervention mission. Results show how the vehicle sets several valve panel configurations throughout the experiment while handling different errors, either spontaneous or induced. Finally, we report the insights gained from our experience and we discuss the main aspects that must be matured and refined in order to promote the future development of intervention autonomous vehicles that can operate, persistently, in subsea facilities.

Keywords

Autonomous underwater vehicles Underwater intervention Persistent autonomy 

Notes

Acknowledgments

This work has been supported by the FP7-ICT-2011-7 project PANDORA-Persistent Autonomy through Learning, Adaptation, Observation and Re-planning (Ref. 288273) funded by the European Commission.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Narcís Palomeras
    • 1
    Email author
  • Arnau Carrera
    • 1
  • Natàlia Hurtós
    • 1
  • George C. Karras
    • 2
  • Charalampos P. Bechlioulis
    • 2
  • Michael Cashmore
    • 3
  • Daniele Magazzeni
    • 3
  • Derek Long
    • 3
  • Maria Fox
    • 3
  • Kostas J. Kyriakopoulos
    • 2
  • Petar Kormushev
    • 4
  • Joaquim Salvi
    • 1
  • Marc Carreras
    • 1
  1. 1.Computer Vision and Robotics Group (VICOROB)University of GironaGeronaSpain
  2. 2.School of Mechanical EngineeringNational Technical University of AthensAthensGreece
  3. 3.King’s College LondonLondonUK
  4. 4.Department of Advanced RoboticsIstituto Italiano di TecnologiaGenoaItaly

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