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Networked and Cooperating Robots for Urban Hygiene

Projektbeschreibung


Advanced Robotics
The DustBot project is aimed at designing, developing, testing and demonstrating a system for improving the management of urban hygiene based on a network of autonomous and cooperating robots, embedded in an Ambient Intelligence infrastructure.

The DustBot project is aimed at designing, developing and testing a system for improving the management of urban hygiene based on a network of autonomous and cooperating robots, embedded in an Ambient Intelligence infrastructure.

The robots will be able to operate in partially unstructured environments (such as squares, streets, parks, etc.) and to vacuumclean them from rubbish and dirt. They will be able to transport small quantities of home garbage, collected on demand from citizens, at their doors. By using preloaded information on the environment (e.g. area maps) and inputs from on-board and external sensory systems, and by taking advantage of the benefits provided by the Ambient Intelligence platform, the robot will be able to move with a proper (and selectable) level of autonomy to carry out its tasks.

The robots will be also equipped with multiple sensors for the monitoring of air (e.g. nitrogen oxides ?NOx-; sulphur oxides ?SOx-; ozone -O3-, benzene, COx, etc.), giving in real time information on the environmental quality in real time. Robots will work as mobile stations, which will monitor pollutants levels in highly populated areas (as well as pedestrian, central areas). Acquired data will be also transferred onto dedicated databases by utilizing the features of the ubiquitous communications network.

The robots and sensors will be part of an Ambient Intelligence platform, which will integrate not only sensors and tools for monitoring the environment and robot tasks execution, but also communications backhaul systems during clean up/emergency operations, databases technologies, knowledge discovery in databases (KDD) processes for extracting and increasing knowledge on urban hygiene management. Following the computation on stored data, feedback will be sent back to human actors (supervisors, decision makers, such as municipality managers, etc.) and/or artificial actuators, in order to perform actions.

The DustBot project is aimed at designing, developing and testing a system for improving the management of urban hygiene based on a network of autonomous and cooperating robots, embedded in an Ambient Intelligence infrastructure.The robots will be able to operate in partially unstructured environments (such as squares, streets, parks, etc.) and to vacuumclean them from rubbish and dirt. They will be able to transport small quantities of home garbage, collected on demand from citizens, at their doors. By using preloaded information on the environment (e.g. area maps) and inputs from on-board and external sensory systems, and by taking advantage of the benefits provided by the Ambient Intelligence platform, the robot will be able to move with a proper (and selectable) level of autonomy to carry out its tasks. The robots will be also equipped with multiple sensors for the monitoring of air (e.g. nitrogen oxides ?NOx-; sulphur oxides ?SOx-; ozone -O3-, benzene, COx, etc.), giving in real time information on the environmental quality in real time. Robots will work as mobile stations, which will monitor pollutants levels in highly populated areas (as well as pedestrian, central areas). Acquired data will be also transferred onto dedicated databases by utilizing the features of the ubiquitous communications network. The robots and sensors will be part of an Ambient Intelligence platform, which will integrate not only sensors and tools for monitoring the environment and robot tasks execution, but also communications backhaul systems during clean up/emergency operations, databases technologies, knowledge discovery in databases (KDD) processes for extracting and increasing knowledge on urban hygiene management. Following the computation on stored data, feedback will be sent back to human actors (supervisors, decision makers, such as municipality managers, etc.) and/or artificial actuators, in order to perform actions.

Wissenschaftliches Gebiet (EuroSciVoc)

CORDIS klassifiziert Projekte mit EuroSciVoc, einer mehrsprachigen Taxonomie der Wissenschaftsbereiche, durch einen halbautomatischen Prozess, der auf Verfahren der Verarbeitung natürlicher Sprache beruht. Siehe: Das European Science Vocabulary.

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FP6-2005-IST-6
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STREP - Specific Targeted Research Project

Koordinator

SCUOLA SUPERIORE DI STUDI UNIVERSITARI E DI PERFEZIONAMENTO SANT'ANNA
EU-Beitrag
€ 533 500,00
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Viale Rinaldo Piaggio, 34
56025 Pontedera
Italien

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Aktivitätstyp
Higher or Secondary Education Establishments
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