Qualitative multi-sensor data fusion

Quantitative methods for data sensor fusion and mobile robot navigation, although paying a high computational cost, have succeeded in their tasks until now. In contrast, qualitative methods for robot navigation and path planning have appeared, showing how robots could reason as intelligent beings. These methods have not been applied to physical robots up to now, but promising advances in Artificial Intelligence are being made. However, very little research has been done to make robots perceive and integrate their sensory information as humans do. This paper shows a hybrid model for multi-sensor data fusion based on a qualitative representation of areas and distances approximately resembling the interpretation made by human beings.