Sound Source Localization for HRI Using FOC-Based Time Difference Feature and Spatial Grid Matching

In human-robot interaction (HRI), speech sound source localization (SSL) is a convenient and efficient way to obtain the relative position between a speaker and a robot. However, implementing a SSL system based on TDOA method encounters many problems, such as noise of real environments, the solution of nonlinear equations, switch between far field and near field. In this paper, fourth-order cumulant spectrum is derived, based on which a time delay estimation (TDE) algorithm that is available for speech signal and immune to spatially correlated Gaussian noise is proposed. Furthermore, time difference feature of sound source and its spatial distribution are analyzed, and a spatial grid matching (SGM) algorithm is proposed for localization step, which handles some problems that geometric positioning method faces effectively. Valid feature detection algorithm and a decision tree method are also suggested to improve localization performance and reduce computational complexity. Experiments are carried out in real environments on a mobile robot platform, in which thousands of sets of speech data with noise collected by four microphones are tested in 3D space. The effectiveness of our TDE method and SGM algorithm is verified.