Ultrasonic sensors have been widely used in recognizing the working environment for a mobile robot. However, their intrinsic problems, such as the specular reflection, the wide beam angle, and the slow propagation velocity, require an excessive number of sensors to be integrated to achieve the various sensing goals. This paper proposes new measurement scheme which uses only two sets of ultrasonic sensors to determine the location and the type of target surface. By measuring the time difference between the returned signals from the target surface, which are generated by two transmitters with 1 ms difference, it classifies type and determines the pose of the target surface. Since the proposed sensor system uses only the two sets of ultrasonic sensors to recognize and localize the target surface, it significantly simplifies the sensing system and reduces the signal processing time so that the working environment can be recognized in real time.

An optimal sensing strategy for an optical proximity sensor system engaged in the recognition and localization of 3D natural quadric objects is presented. The optimal sensing strategy consists of the selection of an optimal beam orientation and the determination of an optimal probing plane that compose an optimal data collection operation known as an optimal probing. The decision of an optimal probing is based on the measure of discrimination power of a cluster of surfaces on a multiple interpretation image, where the measure of discrimination power is defined in terms of a utility function computing the expected number of interpretations that can be pruned out by a probing. An object representation suitable for active sensing based on a surface description vector distribution graph and hierarchical tables is presented. Experimental results are shown.>