Neural processing of airborne sonar for mobile robot applications

Abstract

Describes a range of neural signal processing methods employed for B-Scan ultrasonic image enhancement and material identification. All approaches assume no a-priori knowledge of the environment. A Multi-Layered Perceptron (MLP) employing back propagation learning was used for all aspects of this research. The motivation for this work arises from a requirement to map and navigate within, hazardous environments. Ultrasonic transducers have advantages in such circumstances due to their mechanical robustness and low replacement cost.