DocumentCode :
1928934
Title :
Generating structure in sensory data through coordinated motor activity
Author :
Spoms, O. ; Pegors, Teresa
Author_Institution :
Dept. of Psychol., Indiana Univ., Bloomington, IN, USA
Volume :
4
fYear :
2003
fDate :
20-24 July 2003
Abstract :
Evidence from human and animal studies suggests that neural and cognitive development unfolds in the course of active exploration of the sensory environment. We argue that the statistical structure of sensory inputs depends critically on coordinated motor activity (Lungarella, and Pfeifer, 2001). We develop a set of statistical measures to objectively characterize streams of sensory data from an information theoretical perspective and apply these measures to data sets obtained by adopting different motor strategies. The robotic platform used in the presented experiments consist of a color CCD camera mounted on a 2 DOF pan-tilt unit. Camera images were captured using a standard frame grabber and saved and processed within Matlab. Motor commands instructing the pan and tilt servos to move to specified positions were issued via a serial line interface (rate 2/sec). The stimulus was a "color Mondrian" composed of small color patches of a broad range of colors. A typical experimental run resulted in continuous time series of thousands of images, acquired under constant illumination and spatially averaged to yield a resolution of 16 × 12 pixels, with one image each for the red, green and blue channels of the color camera. Three different motor strategies were used to move the camera: 1) "still": the camera was moved to a random location within the color stimulus and fixed there. 2) "random": the camera was moved at random within a defined region of the stimulus. 3) "foveation": the camera was controlled by a simple neural network to foveate on red patches within the stimulus array. In these preliminary experiments, high complexity of sensory data is the result of a coordinated motor strategy (foveation) and active selection of specific sensory patterns present in the environment. This selection process generates correlations among parts of the image that are the result of dynamic coupling between the robot and the stimulus. Such correlations may serve as a basis for neural plasticity and development.
Keywords :
CCD image sensors; neural nets; robot vision; robots; 2 DOF pan-tilt unit; Matlab; camera image capture; cognitive development; color CCD camera; color Mondrian; coordinated motor activity; coordinated motor strategy; foveation; image correlations; motor commands; neural development; neural network; neural plasticity; robotic platform; sensory data; sensory environment; serial line interface; small color patches; standard frame grabber; statistical measures; Animal structures; Cameras; Charge coupled devices; Charge-coupled image sensors; Humans; Robot kinematics; Robot sensing systems; Robot vision systems; Servomotors; Streaming media;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-7898-9
Type :
conf
DOI :
10.1109/IJCNN.2003.1224013
Filename :
1224013
Link To Document :
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