DIPLECS
Dynamic Interactive Perception-action LEarning in Cognitive Systems
| Coordinatore | LINKOPINGS UNIVERSITET
Organization address
address: CAMPUS VALLA 1 contact info |
| Nazionalità Coordinatore | Sweden [SE] |
| Totale costo | 3˙496˙111 € |
| EC contributo | 2˙600˙000 € |
| Programma | FP7-ICT
Specific Programme "Cooperation": Information and communication technologies |
| Code Call | FP7-ICT-2007-1 |
| Funding Scheme | CP |
| Anno di inizio | 2007 |
| Periodo (anno-mese-giorno) | 2007-12-01 - 2010-11-30 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 | LINKOPINGS UNIVERSITET | SE | coordinator | 0.00 |
| 2 |
ASSOCIATION POUR LA RECHERCHE ET LE DEVELOPPEMENT DES METHODES ET PROCESSUS INDUSTRIELS - ARMINES
Organization address
address: BOULEVARD SAINT-MICHEL 60 contact info |
FR (PARIS 6) | participant | 0.00 |
| 3 |
AUTOLIV DEVELOPMENT AB
Organization address
address: WALLENTINSVAGEN 22 contact info |
SE (VARGARDA) | participant | 0.00 |
| 4 |
CESKE VYSOKE UCENI TECHNICKE V PRAZE
Organization address
address: ZIKOVA 4 contact info |
CZ (PRAHA 6) | participant | 0.00 |
| 5 |
ECOLE NATIONALE SUPERIEURE DES MINES DE PARIS
Organization address
address: BOULEVARD SAINT MICHEL contact info |
FR (PARIS) | participant | 0.00 |
| 6 |
THE UNIVERSITY OF SURREY
Organization address
address: STAG HILL contact info |
UK (GUILDFORD) | participant | 0.00 |
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Obiettivo del progetto (Objective)
The DIPLECS project aims at designing an Artificial Cognitive System architecture that allows for learning and adapting hierarchical perception-action cycles in dynamic and interactive real-world scenarios. The architectural progress will be evaluated within the scenario of a driver assistance system that continuously improves its capabilities by observing the human driver, the car data, and the environment.nThe system is expected to emulate and predict the behaviour of the driver, to extract and analyse relevant information from the environment, and to predict the future state of the car in relation to its context in the world. Starting from a rudimentary, pre-specified, i.e., man-modelled system, the architecture is expected to successively replace manually modelled knowledge with learned models, thus improving robustness and flexibility. Bootstrapping and learning is applied at all levels, in a dynamic and interactive context.nDynamic and interactive context means that the system needs to react at any time to any relevant event and that the action comprises communication to the human driver or direct car control. The architecture applies a hierarchical design principle, where adjacent levels are connected by feedback-loops that require time for processing. Therefore, the potential reaction becomes more advanced through time, i.e., the system provides nested strategies. A real-time operation requires feed-forward mappings, which use the information learned in feedback operation.nThe developed methods will be evaluated in three different settings: off-line with data recorded in a real vehicle, online in the real vehicle, and online for a model car. The first setting allows for evaluating methods that take into account the dynamics of the environment, but which are not real-time capable. The second setting allows for testing of passive assistance capabilities by communicating real-time information. The third setting allows for testing of active capabilities.