State-based sensor fusion for surveillance

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Abstract
This paper presents a state-based control scheme for sensor fusion in autonomous mobile robots. States specify the sensing strategy for each sensor; the feedback rule to be applied to the sensors; and a set of failure conditions, which signal abnormal or inconsistent evidence. Experiments were conducted in the surveillance domain, where the robot was to determine if three different areas in a cluttered tool room remained unchanged after each visit. The data collected from four sensors (a Sony Hi8 color camcorder, a Pulnix black and white camera, an Inframetrics true infrared camera, and Polaroid ultrasonic transducers) and fused using the sensor fusion effects architecture (SFX) support the claims that the state-based control scheme produces percepts which are consistent with the scene being viewed, can improve the global belief in a percept, can improve the sensing quality of the robot, and it robust under a variety of conditions.

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