Makarov, Valeri A. and Castellanos, Nazareth P. and Patane, Luca and Velarde, Manuel G. (2007) Sensory-motor neural loop discovering statistical dependences among imperfect sensory perception and motor response. In Bioengineered and Bioinspired Systems III. Proceedings of SPIE (6592 ). SPIE-INT SOC OPTICAL ENGINEERING, BELLINGHAM. ISBN 978-0-8194-6720-1
Common design of a robot searching for a target emitting sensory stimulus (e.g. odor or sound) makes use of the gradient of the sensory intensity. However, the intensity may decay rapidly with distance to the source, then weak signal-to-noise ratio strongly limits the maximal distance at which the robot performance is still acceptable. We propose a simple deterministic platform for investigation of the searching problem in an uncertain environment with low signal to noise ratio. The robot sensory layer is given by a differential sensor capable of comparing the stimulus intensity between two consecutive steps. The sensory output feeds the motor layer through two parallel sensory-motor pathways. The first "reflex" pathway implements the gradient strategy, while the second "integrating" pathway processes sensory information by discovering statistical dependences and eventually correcting the results of the first fast pathway. We show that such parallel sensory information processing allows greatly improve the robot performance outside of the robot safe area with high signal to noise ratio.
|Item Type:||Book Section|
Conference on Bioengineered and Bioinspired Systems III. Maspalomas, SPAIN. MAY 02-04, 2007. SPIE Europe.
|Uncontrolled Keywords:||Target searching strategy; Short time memory; Dynamical systems; Reflex pathway; Robot|
|Subjects:||Sciences > Computer science > Computer programming|
|Deposited On:||16 Oct 2012 08:11|
|Last Modified:||28 Jun 2016 14:28|
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