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Object Detection in Biosonar Based Robot Navigation

This paper addresses the problem of object detection in a biosonar based mobile robot in a natural environment. In our previous work [9] we presented a time resolved spectrum kernel to extract the similarities between subsequences of the echoes reflected by different trees and we could get higher accuracy than methods which used specific features in all echoes. In this paper we present a more general kernel called warped time-resolved spectrum kernel which considers warping in the subsequences. Furthermore, having a set of those kernels for different size of subsequences, we find the optimal kernel selection via maximizing the Kernel Fisher Discriminant criterion (KFD) to build the optimal linear combination of kernels. We compare the obtained results with our previous work.