Lightweight Multi-direction-of-arrival Estimation on a Mobile Robotic Platform

Knowledge of how many users are there in the environment, and where they are located is essential for natural and efficient Human-Robot Interaction (HRI). However, carry- ing out the estimation of multiple Directions-of-Arrival (multi- DOA) on a mobile robotic platform involves a greater challenge as the mobility of the service robot needs to be considered when proposing a solution. This needs to strike a balance with the performance of the DOA estimation, specifically the amount of users the system can detect, which is usually limited by the amount of microphones used. In this paper, a lightweight hardware system (based on a 3-microphone triangular system) is used, and a fast multi-DOA estimator is proposed that is able to estimate more users than the number of microphones employed. Index Terms—direction of arrival, service robots, triangular array, lightweight, robust

[1]  Jean Rouat,et al.  Enhanced robot audition based on microphone array source separation with post-filter , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[2]  Rong Liu,et al.  Azimuthal source localization using interaural coherence in a robotic dog: modeling and application , 2010, Robotica.

[3]  Douglas L. Jones,et al.  Performance of time- and frequency-domain binaural beamformers based on recorded signals from real rooms. , 2004, The Journal of the Acoustical Society of America.

[4]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[5]  Ashutosh Saxena,et al.  Learning sound location from a single microphone , 2009, 2009 IEEE International Conference on Robotics and Automation.

[6]  Barbara Webb,et al.  Robot phonotaxis in the wild: a biologically inspired approach to outdoor sound localization , 2004, Adv. Robotics.

[7]  C. Faller,et al.  Source localization in complex listening situations: selection of binaural cues based on interaural coherence. , 2004, The Journal of the Acoustical Society of America.

[8]  Douglas L. Jones,et al.  Localization of multiple acoustic sources with small arrays using a coherence test. , 2008, The Journal of the Acoustical Society of America.

[9]  Alexander H. Waibel,et al.  Enabling Multimodal Human–Robot Interaction for the Karlsruhe Humanoid Robot , 2007, IEEE Transactions on Robotics.

[10]  Andreas Stolcke,et al.  Observations on overlap: findings and implications for automatic processing of multi-party conversation , 2001, INTERSPEECH.

[11]  Carlos Gershenson,et al.  IOCA: An Interaction-Oriented Cognitive Architecture , 2011 .

[12]  Joaquim Llisterri,et al.  The Corpus DIMEx100: transcription and evaluation , 2010, Lang. Resour. Evaluation.

[13]  Erik Hjelmås,et al.  Face Detection: A Survey , 2001, Comput. Vis. Image Underst..

[14]  Illah R. Nourbakhsh,et al.  A survey of socially interactive robots , 2003, Robotics Auton. Syst..

[15]  Anju Vyas Print , 2003 .

[16]  Luis Alberto Pineda,et al.  Robotic Orientation towards Speaker for Human-Robot Interaction , 2010, IBERAMIA.

[17]  Hiroaki Kitano,et al.  Real-time sound source localization and separation for robot audition , 2002, INTERSPEECH.

[18]  D. Wang,et al.  Computational Auditory Scene Analysis: Principles, Algorithms, and Applications , 2008, IEEE Trans. Neural Networks.

[19]  David Thompson,et al.  Noise source identification using microphone arrays , 2007 .