Increasing the autonomy levels for underwater intervention missions by using learning and probabilistic techniques

Jorge Sales, Luís Santos, Pedro J. Sanz, Jorge Dias, J. C. García

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


This paper represents research in progress in autonomous manipulation for underwater intervention missions within the context of the GRASPER project. This project focuses on developing manipulation skills for an Autonomous Underwater Vehicle (AUV). Current research in underwater robotics intends to increase autonomy for all kinds of robotic intervention operations that require physical interaction. Very few underwater systems have the capacity to carry out intervention without any kind of umbilical cables for tele-operating the actions. This article aims to investigate new approaches to follow with the aforementioned challenges, with the inclusion of learning and probabilistic techniques to increase the autonomy levels of an underwater manipulation system. With this goal, a collaboration research action has been established between the IRSLab at UJI (Spain), as experts in the underwater robotic manipulation domain, and the Institute of Systems and Robotics from University of Coimbra (Portugal), experts in learning by interaction within a robotic manipulation context.

Original languageBritish English
Title of host publicationROBOT2013
Subtitle of host publication1st Iberian Robotics Conference - Advances in Robotics
EditorsAlberto Sanfeliu, Manuel Ferre, Manuel A. Armada
PublisherSpringer Verlag
Number of pages16
ISBN (Electronic)9783319034126
StatePublished - 2014
EventROBOT 2013: 1st Iberian Robotics Conference - Madrid, Spain
Duration: 28 Nov 201329 Nov 2013

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357


ConferenceROBOT 2013: 1st Iberian Robotics Conference


  • Bayesian Learning
  • Dynamic Bayesian Network
  • Underwater Autonomous Intervention
  • UWSim underwater realistic simulator


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