Noptilus
Noptilus 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 & 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 Leixões, utilizing a team of 6 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-the-optimal performance.
NOPTILUS main objective is to determine – fully-autonomously & in real-time – the AUVs’ trajectories/behavior that maximize situation awareness subject to the severe communication, sensing & environmental limitations
Full Title: autoNomous, self-Learning, OPTImal and compLete Underwater Systems
Funded by: EU-FP7, ICT-2009.6
Start-End Date: 01/04/2011 – 01/04/2015