Related Projects

subCULTron: Submarine cultures perform long-term robotic exploration of unconventional environmental niches

subCULTron aims for achieving long-term autonomy in a learning, self-regulating, self-sustaining underwater society/culture of robots in a high-impact application area: Venice, Italy.

Our heterogeneous system consists of 3 different agent types: On the sea-ground, artificial mussels are the collective long-term memory of the system, allowing information to stay beyond the runtime of other agents, thus allowing to continue learning from previously learned states. These mussels monitor the natural habitat, including biological agents like algae, bacterial incrustation and fish. On the water surface, artificial lily pads interface with the human society, delivering energy and information influx from ship traffic or satellite data. Between those two layers, artificial fish move/monitor/explore the environment and exchange info with the mussels and lily pads. Artificial mussels are novel class of underwater agents.

We aim to push forward the edge of knowledge with novel sensors (electric sense/electro-communication), novel bio-inspired algorithms (underwater hives) and novel energy harvesting in underwater scenarios. We will improve the world’s record for swarm-size in autonomous collective underwater robotics by almost one order of magnitude.

Our application field is a human- and animal-co-inhabited real-world environment of high impact: Venice canals & lagoon. These habitats are highly dynamic and structured, expected to be reflected by a spatial self-structuring of our mussel population. These sub-populations locally perform memetic or cultural learning algorithms on their specific local data. Thus our cultural evolution algorithms will promote sub-culture development, similar to the human society that does the same above the water level in parallel.

Overall, we aim for an artificial society underneath the water-surface to the service of a human society above the water.

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Here is a (not yet complete) list of related projects, associated with us by the Awareness Coordination Action, which is supporting research under the FP7: FET Proactive Intiative: Self-Awareness in Autonomic Systems (Awareness). The CA is a 3 year project: 2010 – 2013.

ASCENS: Autonomic Service-Component Ensembles

The ASCENS project focus on service-component ensembles (SCEs), hierarchical ensembles built from service components (SCs), simpler SCEs and knowledge units (K) connected via highly dynamic infrastructure.

Service components are nodes that can cooperate, with different roles, in an open and non-deterministic environment. A service-component ensemble is a set of service components with dedicated knowledge units, to represent shared local and global knowledge basis about levels of awareness, resources, connectivity and networking, interconnected in a dynamic network, featuring goal-oriented, safe and secure execution and efficient resource management.

To build ensembles of service components, whose properties go far beyond the state of the art in current software engineering and technology, the following domains are thoroughly investigated within the scope of the project:
Linguistic support for programming SCEs, expressing awareness and exchanging knowledge, formalization and modeling the fundamental SCE network properties like autonomous behavior and aware-rich networking, knowledge representation and self-awareness of service components, methods and mechanisms for adaptation and dynamic self-expression, techniques and methodology for the design and development of reliable SCs and SCEs and their verification using formal methods, software infrastructure with a set of tools to support programming, deployment and execution of SCE-based applications. A set of case studies (from robotics, cloud computing and e-Vehicles) are used to illustrate the wide coverage of the ASCENS approach.

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SAPERE: Self-aware Pervasive Service Ecosystems

The objective of SAPERE is the development of a highly-innovative theoretical and practical framework for the decentralized deployment and execution of self-aware and adaptive services for future and emerging pervasive network scenarios. The framework will be grounded on a foundational re-thinking of current service models and of associated infrastructures and algorithms. In particular, getting inspiration from natural ecosystems, the project will demonstrate and experiment the possibility of modelling and deploying services as autonomous individuals in an ecosystem of other services, data sources, and pervasive devices, and of enforcing self-awareness and autonomic behaviours as inherent properties of the ecosystem, rather than as peculiar characteristics of its individuals only.

The specific objectives that will be pursued in a tightly orchestrated way by the proposal, each contributing to the overall definition of the integrated SAPERE framework, include:

  • Defining an innovative model for service and data components in the ecosystem, based on a simple concept of self-aware components and a general nature-inspired interaction model
  • Studying and experimenting decentralized self-* algorithms to enforce various forms of spatial selforganization, self-composition, and self-management for data and services in the ecosystem
  • Studying and experimenting solutions to support advanced management of data and situation identification, to inject advanced forms of present- and future-awareness in the ecosystem
  • Implementing an innovative, lightweight and modular infrastructure for the deployment and execution of services, and for the management of contextual data items

The effectiveness of the proposed solutions and of the overall SAPERE framework will be experienced and evaluated in selected use cases in the area of “adaptive and decentralized pervasive services”. The project will be carried on by a consortium with complementary competences, will last three years, and will touch prominently but not exclusively the “Creating awareness” topic of the “Self-awareness in autonomic systems” call.

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SYMBRION: Symbiotic Evolutionary Robot Organisms

The main focus of this project is to investigate and develop novel principles of adaptation and evolution for symbiotic multi-robot organisms based on bio-inspired approaches and modern computing paradigms. Such robot organisms consist of super-large-scale swarms of robots, which can dock with each other and symbiotically share energy and computational resources within a single artificial-life-form. When it is advantageous to do so, these swarm robots can dynamically aggregate into one or many symbiotic organisms and collectively interact with the physical world via a variety of sensors and actuators. The bio-inspired evolutionary paradigms combined with robot embodiment and swarm-emergent phenomena, enable the organisms to autonomously manage their own hardware and software organization. In this way, artificial robotic organisms become self-configuring, self-healing, self-optimizing and self-protecting from both hardware and software perspectives. This leads not only to extremely adaptive, evolve-able and scalable robotic systems, but also enables robot organisms to reprogram themselves without human supervision and for new, previously unforeseen, functionality to emerge. In addition, different symbiotic organisms may co-evolve and cooperate with each other and with their environment.

For more information see: