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Cognitive system for autonomous underwater intervention

The implementation of autonomous intervention tasks with underwater vehicles is a non-trivial issue due to the challenging and dynamic conditions of the underwater medium (e.g., water current perturbations, water visibility). Likewise, it requires a significant programming effort each time that the vehicle must perform a different manipulation operation. In this paper we propose, instead, to use a cognitive system that learns the intervention task from an expert operator through an intuitive learning by demonstration (LbD) algorithm. Taking as an input few operator demonstrations, the algorithm generalizes the task knowledge into a model and is able to control the vehicle and the manipulator simultaneously to reproduce the task, thus conferring a more adaptive behavior in front of the environment changes and allowing to easily transfer the knowledge of new tasks. A cognitive architecture has been implemented in order to integrate the LbD algorithm with the onboard sensors and actuators and to allow its interplay with the vehicle perception, control and navigation modules. To validate the full framework we present real experiments in a water tank using an AUV equipped with a four DoF manipulator. A human operator teaches the system to perform a valve turning intervention and we analyze the results of multiple task reproductions, including cases under the effect of water current perturbations, showing the success of the system in autonomously reproducing the task

This research was sponsored by the Spanish Government (CO-MAROBProject, DPI2011-27977-C03-02) and the PANDORAEUFP7-Project under the grant agreementFP7-ICT-2011-7288273

© Pattern Recognition Letters, 2015, vol. 67, núm. 1, p. 91-99

Elsevier

Autor: Carrera Viñas, Arnau
Palomeras Rovira, Narcís
Hurtós Vilarnau, Natàlia
Kormushev, Petar
Carreras Pérez, Marc
Data: 2015
Resum: The implementation of autonomous intervention tasks with underwater vehicles is a non-trivial issue due to the challenging and dynamic conditions of the underwater medium (e.g., water current perturbations, water visibility). Likewise, it requires a significant programming effort each time that the vehicle must perform a different manipulation operation. In this paper we propose, instead, to use a cognitive system that learns the intervention task from an expert operator through an intuitive learning by demonstration (LbD) algorithm. Taking as an input few operator demonstrations, the algorithm generalizes the task knowledge into a model and is able to control the vehicle and the manipulator simultaneously to reproduce the task, thus conferring a more adaptive behavior in front of the environment changes and allowing to easily transfer the knowledge of new tasks. A cognitive architecture has been implemented in order to integrate the LbD algorithm with the onboard sensors and actuators and to allow its interplay with the vehicle perception, control and navigation modules. To validate the full framework we present real experiments in a water tank using an AUV equipped with a four DoF manipulator. A human operator teaches the system to perform a valve turning intervention and we analyze the results of multiple task reproductions, including cases under the effect of water current perturbations, showing the success of the system in autonomously reproducing the task
This research was sponsored by the Spanish Government (CO-MAROBProject, DPI2011-27977-C03-02) and the PANDORAEUFP7-Project under the grant agreementFP7-ICT-2011-7288273
Format: application/pdf
ISSN: 0167-8655
Accés al document: http://hdl.handle.net/10256/12496
Llenguatge: eng
Editor: Elsevier
Col·lecció: MICINN/PN 2012-2014/DPI2011-27977-C03-02
Reproducció digital del document publicat a: http://dx.doi.org/10.1016/j.patrec.2015.06.010
Articles publicats (D-ATC)
info:eu-repo/grantAgreement/EC/FP7/288273
És part de: © Pattern Recognition Letters, 2015, vol. 67, núm. 1, p. 91-99
Drets: Tots els drets reservats
Matèria: Underwater intervention
Vehicles submergibles
Submersibles
Robots -- Sistemes de control
Robots -- Control systems
Robots submarins
Underwater robots
Títol: Cognitive system for autonomous underwater intervention
Tipus: info:eu-repo/semantics/article
Repositori: DUGiDocs

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