Mobile Robot Sonar for Target Localization and Classification

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Abstract
A novel sonar array is presented that has applications in mobile robotics for localization and mapping of indoor en vironments. The ultrasonic sensor localizes and classifies multiple targets in two dimensions to ranges of up to 8m. By accounting for effects of temperature and humidity, the sys tem is accurate to within 1 mm and 0.1° in still air. Targets separated by 10 mm in range can be discriminated. The error covariance matrix for these measurements is derived to allow fusion with other sensors. Targets are statistically classified into four reflector types: planes, corners, edges, and unknown. This article establishes that two transmitters and two re ceivers are necessary and sufficient to distinguish planes, corners, and edges. A sensor array is presented with this minimum number of transmitters and receivers. A novel de sign approach is used such that the receivers are closely spaced so as to minimize the correspondence problem of as sociating different receiver echoes from multiple targets. A linear filter model for pulse transmission, reception, air absorption, and dispersion is used to generate a set of tem plates for the echo as a function of range and bearing angle. The optimal echo arrival time is estimated from the maximum cross-correlation of the echo with the templates. The use of templates also allows overlapping echoes and disturbances to be rejected. Noise characteristics are modeled for use in the maximum likelihood estimates of target range and bearing. Experimental results are presented to verify assumptions and characterize the sensor.

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