Biological and cognitive foundations of intelligent sensor fusion

Abstract

This paper reviews the literature from the biological and cognitive sciences in sensory integration and derives principles for use in constructing intelligent sensor fusion systems. In particular, it presents psychophysical and neurophysical studies on how sensor fusion is accomplished and cognitive models of associated activities, including optimization of sensing configurations, improvement of sensing quality, and filtering of noise. The sensor fusion effects architecture for robot navigation is also presented as one example of how these insights from the biological and computer science can be applied to robotic sensor fusion. Experimental results demonstrates the utility of the biological and cognitive insights, especially that of fusion modes. Other representative architectures for robotic sensor fusion are contrasted with the biological and cognitive principles.