Recently, interest on artificial robot audition is growing for developing human-robot interaction. The main purposes of an artificial audio system mounted on mobile robot are localizing sound sources, separating speech signal that is relevant to a particular speaker such as robot's master, and processing speech sources to extract useful information such as master's uttering commands. This paper reports a novel proposed method of a speaker's direction tracking algorithm, and a realization of the real tracking system on a mobile robot. Basic approach of this study belongs to a category of direction finding known as sparseness-based one which employs time-frequency decomposition and disjoint property between different speech signals. The novel points in the proposed source tracking exist on a reliable data selection from time-frequency cells and the application of mean shift tracking to the kernel density estimator derived from these reliable time-frequency components. A wheel-based mobile robot is developed and built-in audio processing system. Experiments are conducted and demonstrate the ability to localize in real environments.