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SPATIAL TEMPORAL PATTERNS FOR ACTION-ORIENTED PERC.. (SPARK II)
SPATIAL TEMPORAL PATTERNS FOR ACTION-ORIENTED PERCEPTION IN ROVING ROBOTS II: AN INSECT BRAIN COMPUTATIONAL MODEL
(SPARK II)
Date du début: 1 févr. 2008,
Date de fin: 31 janv. 2011
PROJET
TERMINÉ
The aim of SPARK II is to develop, evaluate, optimise and generalise a new, insect brain inspired, computational model. The architecture will be hierarchical, based on parallel sensory-motor pathways, implementing reflex-driven basic behaviours. These will be enriched with higher and complex insect brain structural models (Mushroom Bodies, Central Complex) and more physically-inspired nonlinear lattices. The latters will be able to generate "self-organizing" complex dynamics, while the formers will reproduce relevant cognitive functions in insects such as attention-like processes, short-term memory and rewarding mechanisms. Both of them will work concurrently to generate cognitive behaviours at the output motor layer. The architecture will exploit a number of different sensors, processing signals distributed in space and time and also showing nonlinear dynamics. Perceptual processes are conceived as emerging pattern flows (result of a nonlinear spatial-temporal dynamics). Pattern meaning (concept generation) will be incrementally built upon information derived from sensors as well as from some basic "inherited" behaviours mediated through the environment. Emerged patterns, with the concurrent dynamics generated by models of the relevant perception centres in insects, will influence the particular associated motor behaviour. To show the generality of the approach, the model will be applied to different robotics architectures, asked to work in real life, unstructured, cluttered and dynamically changing environment. This will demonstrate that perception for action, formulated by suitably merging complex systems with dynamics derived by insect brain models, can lead to the emergence of general archetypes of wide applicability.Finally another challenging task will consist in using the same model, applied to different robots, to lead to the emergence of cooperation capabilities to perform tasks unable to be fulfilled by one robot alone: further proof of generality.
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