Autonomous, self-learning, optimal and complete underwater systems (NOPTILUS)

Themes: Sensor network communication, XG - Next Generation Sensing and Communication

Can we develop robust, cooperative and cognitive communication for Autonomous Underwater Vehicles?
Current multi-AUV systems are far from being capable of fully autonomously taking over real-life complex situation-awareness operations. As such operations require advanced reasoning and decision- making abilities the current designs have to heavily rely on human operators. The involvement of humans, however, is by no means a guarantee of performance; humans can easily be overwhelmed by the information overload, fatigue can act detrimentally to their performance, properly coordinating vehicles actions is hard, and continuous operation is all but impossible.

Within NOPTILUS we take the view that an effective fully-autonomous multi-AUV concept/system is capable of overcoming these shortcomings, by replacing human-operated operations by a fully autonomous one. To successfully attain such an objective, significant advances are required, involving cooperative and cognitive-based communications and sonars (low level), Gaussian Process-based estimation as well as perceptual sensory-motor and learning motion control (medium level), and learning/cognitive-based situation understanding and motion strategies (high level).

Of paramount importance is the integration of all these advances and the demonstration of the NOPTILUS system in a realistic environment at the Port of Leixoes, utilizing a team of six AUVs that will be operating continuously on a 24hours/7days-a-week basis. As part of this demonstration another important aspect of the NOPTILUS system - that of (near-)optimality - will be shown.

Evaluation of the performance of the overall NOPTILUS system will be performed with emphasis on its robustness, dependability, adaptability and flexibility especially when it deals with completely unknown underwater environments and situations "never taught before" as well as its ability to provide with arbitrarily-close-to-optimal performance.

Project data

Researchers: Geert Leus, Hamid Ramezani
Starting date: January 2011
Closing date: January 2014
Contact: Geert Leus

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