Merging Ultrasonic Sensor Readings Into A Consistent Environment Model

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Abstract
The algorithm presented in this paper constructs a geometric model of the environment using ultrasonic sensors. To do this in a reliable way, it has to take different error sources into account. Unlike other approaches, where a low-level, pixel based, probabilistic model is constructed to represent the uncertainty arising from false measurements, a high level, geometric, model is constructed. It is shown that a high level model, besides being faster to construct, is more appropriate for taking into account the typical characteristics of ultrasonic sensors. The algorithm detects and eliminates inconsistent measurements by combining evidence gathered from different points of view. This is made possible by extracting from the measurements not only information concerning the position of obstacles, but also information about regions that must be empty when seen from a certain angle. To conclude, some examples of the behaviour of this algorithm in real-world situations are presented.

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