Learning by demonstration applied to underwater intervention

Abstract

Comunicació de congrés presentada a: 17th International Conference of the Catalan Association for Artificial Intelligence, Barcelona, Catalonia, Spain, October 22-24, 2014

Performing subsea intervention tasks is a challenge due to the complexities of the underwater domain. We propose to use a learning by demonstraition algorithm to intuitively teach an intervention autonomous underwater vehicle (IAUV) how to perform a given task. Taking as an input few operator demonstrations, the algorithm generalizes the task into a model and simultaneously controls the vehicle and the manipulator (using 8 degrees of freedom) to reproduce the task. A complete framework has been implemented in order to integrate the LbD algorithm with the different onboard sensors and actuators. A valve turning intervention task is used to validate the full framework through real experiments conducted in a water tank

This research was sponsored by the Spanish government (COMAROB Project, DPI2011-27977-C03-02) and the PANDORA EU FP7-Project under the Grant agreement FP7-ICT-2011-7-288273