Currently involved with:
1) ROAD-, AIR- AND WATER- BASED FUTURE INTERNET EXPERIMENTATION (RAWFIE)
RAWFIE (Road-, Air-, and Water- based Future Internet Experimentation) is a project funded by the European Commission (Horizon H2020 programme) under the Future Internet Research Experimentation (FIRE+) initiative that aims at providing research facilities for Internet of Things (IoT) devices. The project introduces a unique platform across the space and technology by integrating numerous test beds of unmanned vehicles for research experimentation in vehicular, aerial and maritime environments. The platform will support experimenters with smart tools to conduct and monitor experiments in the domains of IoT, networking, sensing and satellite navigation. The project that is bringing together thirteen partner organizations from eight EU countries will organize two open calls to attract researchers from academia and industry, test bed operators and unmanned vehicles manufacturers.
4) SYSTEM-OF-SYSTEMS THAT ACT LOCALLY FOR OPTIMIZING GLOBALLY (Local4Global)
Today’s Technical Systems of Systems (TSoS) such as transport, traffic and energy management systems require the deployment of an expensive-to-deploy and operate sensor and communication infrastructure. Moreover, they need a very time/effort-consuming modelling, analysis and control design procedure in order to achieve an efficient performance. On the contrary, Natural Systems of Systems (NSoS) such as the human brain, animal herds (swarms), teams of interacting/cooperating humans or animals achieve a highly efficient, elegant and supreme functionality without the need of an expensive infrastructure as they primarily rely on local information between neighbouring systems and, most importantly, they do not need any modelling, analysis or control design tools to achieve such a functionality. If the powerful attributes of NSoS were possible to be transferred and embedded into TSoS, this would lead not only to more efficient TSoS operations but, most importantly, to TSoS that are significantly easier, safer and more economical to design, deploy and operate. This is actually the main objective of Local4Global: to develop, test and evaluate a new groundbreaking, generic and fully-functional methodology/system for controlling TSoS which – as in the NSoS case – optimizes the TSoS performance at the global level without the need of deployment and operation of an expensive sensor and communication infrastructure and, most importantly, without the need for the use of elaborate and time/effort consuming modelling, analysis and control design tools.
3) AUTONOMOUS, SELF-LEARNING, OPTIMAL AND COMPLETE UNDERWATER SYSTEMS (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.
2) Sensor Web Fire Shield (SWeFS)
The Sensor Web Fire Shield (SWeFS) research project aims at delivering:
- a methodology for developing a novel Sensor Web platform for dynamic data-driven assimilation (DDDAS) for securing the Wildland-Urban Interface (WUI) zones against environmental risks, and,
- a prototype DDDAS system specifically optimized/tuned for addressing the serious threat of forest fires in Greece. SWeFS calls for multidisciplinary research in the areas of sensor networks, distributed vision systems, remote sensing, geographical information systems (GIS), data stream fusion, space-time predictive modeling and control systems.
The main objectives of the proposed research are:
- Design a novel Sensor Web architecture with heterogeneous sensors, remote sensing and risk prediction models into a closed loop system for the effective and timely detection of environmental risks.
- Test the proposed architecture through the development of a prototype platform for fire detection in WUI zones in Greece.
- Improve the prediction of the spatiotemporal evolution of a hazardous phenomenon by adopting a DDDAS approach for calibrating simulation models in real-time.
1) RAPIDLY-DEPLOYABLE, SELF-TUNING, SELF-RECONFIGURABLE, NEARLY-OPTIMAL CONTROL DESIGN FOR LARGE-SCALE NONLINEAR SYSTEMS (AGILE)
The inability of existing theoretical and practical tools to scaleably and efficiently deal with the control of complex, uncertain and time-changing large-scale systems, not only leads to a effort-, time- and cost-consuming deployment of Large-Scale Control Systems (LSCSs), but also prohibits the wide application of LSCS in areas and applications where LSCSs could potentially have a tremendous effect in improving system efficiency and Quality of Services (QoS), reducing energy consumption and emissions, and improving the day-to-day quality of life. Based on recent advances of its partners on convex design for LSCSs and robust and efficient LSCS self-tuning, the AGILE project aims at developing and evaluating an integrated LSCS-design methodology, applicable to large-scale systems of arbitrary scale, heterogeneity and complexity and capable of:
· Providing pro-active, arbitrarily-close-to-optimal LSCS performance;
· Being intrinsically self-tuneable, able to rapidly and efficiently optimize LSCS performance when short- medium- and long-time variations affect the large-scale system;
· Providing efficient, rapid and safe fault-recovery and LSCS re-configuration; and,
· Achieving all the above, while being scalable and modular.
To ease implementation and deployment of the AGILE system in existing open-architecture SCADA/DCS infrastructures, a set of open-source interfacing tools will be developed. The integrated LSCS design system to be developed within AGILE along with the interfaces will be extensively tested and evaluated into two real-life large-scale Test Cases (a 20-junction urban traffic network and a large-scale energy-controlled building) possessing a rich variety of design and performance characteristics, extremely complex nonlinear dynamics, highly stochastic effects, uncertainties and modeling errors, as well as reconfiguration and modular design requirements.