The automatic acquisition of structured object maps requires sophisticated perceptual mechanisms that enable the robot to recognize the objects that are to be stored in the robot map. This paper investigates a particular object recognition problem: the automatic detection and classification of gateways in office environments based on laser range data. We will propose, discuss, and empirically evaluate a sensor model for crossing gateways and different approaches to gateway classification including simple maximum classifiers and HMM-based classification of observation sequences.
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