Abstract
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 IRS-Lab 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.
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References
Prats, M., Pérez, J., Fernández, J., Sanz, P.: An open source tool for simulation and supervision of underwater intervention missions. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2577–2582 (2012)
Marani, G., Choi, S.K., Yuh, J.: Underwater autonomous manipulation for intervention missions AUVs. Ocean Engineering 36, 15–23 (2009)
Sanz, P.J., Ridao, P., Oliver, G., Casalino, G., Insaurralde, C., Silvestre, C., Melchiorri, C., Turetta, A.: TRIDENT: Recent improvements about autonomous underwater intervention missions. In: 3rd IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles (NGCUV 2012), Porto, Portugal (April 2012)
Sanz, P., Prats, M., Ridao, P., Ribas, D., Oliver, G., Ortiz, A.: Recent progress in the RAUVI project: A Reconfigurable Autonomous Underwater Vehicle for Intervention. In: ELMAR, 2010 Proceedings, pp. 471–474 (2010)
Faria, D., Martins, R., Lobo, J., Dias, J.: Extracting data from human manipulation of objects towards improving autonomous robotic grasping. Robotics and Autonomous Syst., Elsevier: Sp. Issue on Autonomous Grasping 60, 396–410 (2012)
Calinon, S., Guenter, F., Billard, A.: On learning, representing and generalizing a task in a humanoid robot. IEEE Transactions on Systems, Man and Cybernetics, Part B, Special Issue on Robot Learning by Observation, Demonstration and Imitation 37, 286–298 (2007)
Kondo, M., Ueda, J., Ogasawara, T.: Recognition of in-hand manipulation using contact state transition for multifingered robot hand control. Robotics and Autonomous Systems 56(1), 66–81 (2008)
Bernardin, K., Ogawara, K., Ikeuchi, K., Dillmann, R.: A sensor fusion approach for recognizing continuous human grasping sequences using hidden markov models. Trans. Rob. 21(1), 47–57 (2005)
Krger, V., Herzog, D., Baby, S., Ude, A., Kragic, D.: Learning actions from observations. IEEE Robot. Automat. Mag. 17(2), 30–43 (2010)
Bekiroglu, Y., Laaksonen, J., Jrgensen, J.A., Kyrki, V., Kragic, D.: Assessing grasp stability based on learning and haptic data. IEEE Transactions on Robotics 27(3), 616–629 (2011)
Lin, Y., Ren, S., Clevenger, M., 0004, Y.S.: Learning grasping force from demonstration. In: IEEE Int. Conf. on Robotics and Automation ICRA, pp. 1526–1531 (2012)
Lopes, M., Melo, F., Montesano, L.: Active learning for reward estimation in inverse reinforcement learning. In: Buntine, W., Grobelnik, M., Mladenić, D., Shawe-Taylor, J. (eds.) ECML PKDD 2009, Part II. LNCS, vol. 5782, pp. 31–46. Springer, Heidelberg (2009)
Jetchev, N., Toussaint, M.: Task space retrieval using inverse feedback control. In: ICML, pp. 449–456 (2011)
Ratliff, N.D., Bagnell, J.A., Zinkevich, M.A.: Maximum margin planning. In: Proceedings of the 23rd International Conference on Machine Learning (ICML 2006), pp. 729–736. ACM, New York (2006)
Guizzo, E.: Humanoid robot justin learning to fix satellites. IEEE Spectrum, http://spectrum.ieee.org/automaton/robotics/industrial-robots/humanoid-robot-justin-learning-to-fix-satellites
Prats, M., García, J., Fernández, J., Marín, R., Sanz, P.: Advances in the specification and execution of underwater autonomous manipulation tasks. In: 2011 IEEE OCEANS, Spain, pp. 1–5 (2011)
Carrera, A., Ahmadzadeh, S.R., Ajoudani, A., Kormushev, P., Carreras, M., Caldwell, D.G.: Towards Autonomous Robotic Valve Turning. Journal of Cybernetics and Information Technologies (CIT) 12(3), 17–26 (2012)
Prats, M., Fernández, J., Sanz, P.: Combining template tracking and laser peak detection for 3D reconstruction and grasping in underwater environments. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 106–112 (2012)
Bessiere, P., Ahuactzin, J.M., Mekhnacha, K., Mazer, E.: Bayesian Programming. Chapman and Hall/CRC (2013)
Fernández, J.J., Prats, M., García, J.C., Marín, R., Peñalver, A.: Manipulation in the seabed: A new underwater robot arm for shallow water intervention. In: Embedded Systems, Computational Intelligence and Telematics in Control (2012)
García, J.C., Peñalver, A., Prats, M., Sanz, P.J.: Recent progress in HRI for underwater robotic intervention. In: 2013 IEEE International Conference on Robotics and Automation (ICRA 2013), Karlsruhe, Germany (May 2013)
Prats, M., García, J.C., Fernández, J.J., Marín, R., Sanz, P.J.: Towards Specification, Planning and Sensor-Based Control of Autonomous Underwater Intervention. In: Proceedings of the 18th IFAC World Congress, Milano, Italy, pp. 10361–10366 (2011)
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Sales, J., Santos, L., Sanz, P.J., Dias, J., García, J.C. (2014). Increasing the Autonomy Levels for Underwater Intervention Missions by Using Learning and Probabilistic Techniques. In: Armada, M., Sanfeliu, A., Ferre, M. (eds) ROBOT2013: First Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 252. Springer, Cham. https://doi.org/10.1007/978-3-319-03413-3_2
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DOI: https://doi.org/10.1007/978-3-319-03413-3_2
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