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Roughness is a characteristic of a surface that is a function of its geometry. Ultrasonic sensing in air provides range, area, and angle information because the surface geometry determines the characteristics of the echo. The authors introduce the "spatial-angle-filter model" to explain the impact of surface roughness on the echo. On the basis of this model, they design a set of features for use in classifying surfaces. The quality of the features and the classification is measured with the Mahalanobis distance. The resultant system is able to achieve 99.73% classification of a set of 12 surfaces using five features. Abstract-Roughness is a characteristic of a surface that is a function of its geometry. Ultrasonic sensing in air provides range, area, and angle information because the surface geometry determines the characteristics of the echo. The authors introduce the "spatial-angle-filter model" to explain the impact of surface roughness on the echo. On the basis of this model, they design a set of features for use in classifying surfaces. The quality of the features and the classification is measured with the Mahalanobis distance. The resultant system is able to achieve 99.73% classification of a set of 12 surfaces using five features. Disciplines Physical Sciences and MathematicsIndex Terms-Continuous transmission frequency modulated (CTFM) ultrasonic sensor, Mahalanobis classifier, spatial-angle filter, surface roughness, ultrasonic sensing, wheeled mobile robot.

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Data fusion is the process of combining signals from several sensors into a single world view. A four-level software architecture provides a generalised h e w o r k for designing data fusion systems. Important issues in data fusion are feature extraction, closure criteria, paradigm shifts between levels, error correction and knowledge engineering. Each of these is discussed in the context of a data fusion system for ultrasonic mapping with a mobile robot.

Mobile robots navigate through m a y environments that include plants. A sensor that can recognise plants would be usej2 for navigation in these environments. Two problems make plant sensing dificult: plant similarity and plant asymmetry with rotation.A CTFM ultrasonic sensor produces a signal that contains information about the geometric structure of plants.Correlation of echoes from many orientations show that plants can be recognised with suflcient accuracy for navigation.