Paper
22 May 2007 Sensory-motor neural loop discovering statistical dependences among imperfect sensory perception and motor response
Author Affiliations +
Proceedings Volume 6592, Bioengineered and Bioinspired Systems III; 65920I (2007) https://doi.org/10.1117/12.724327
Event: Microtechnologies for the New Millennium, 2007, Maspalomas, Gran Canaria, Spain
Abstract
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nazareth P. Castellanos, Valeri A. Makarov, Luca Patané, and Manuel G. Velarde "Sensory-motor neural loop discovering statistical dependences among imperfect sensory perception and motor response", Proc. SPIE 6592, Bioengineered and Bioinspired Systems III, 65920I (22 May 2007); https://doi.org/10.1117/12.724327
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KEYWORDS
Sensors

Signal to noise ratio

Robotic systems

Data processing

Environmental sensing

Space robots

Dynamical systems

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