Bearing-only Simultaneous Localization and Mapping (SLAM) is a partially observable SLAM problem, in wich the sensor used for perceiving the robot‘s enviroment, provides only-angular information respect to the landmarks, and therefore does not give enough information to compute the full state of a landmark from a single observation. In this context, vision-based systems have also gained a great interest in the robotics community. Nevertheless the use of “sound sources” as map’s features have been very little explored in SLAM. In this work a method for performing SLAM with sound sources is presented. A robot capable of sense bearing information respect to an external sound source with modest angular acuity ( − 10°) is considered.At the robot trajectory start, the sound source position is unknown; while the robot moves, the position of the sound source and the robot position in a global coordinate frame are both estimated. Experimental results with simulations and with a real robot demonstrate that tracking a unique source sound is enough to reasonably correct the odometry information provided by the encoders.


SLAM Sound Sources Bearing Sensors 


  1. 1.
    Valin, J., Michaud, F., Rouat, J., Lètourneau, D.: Robust sound source localization using a microphone array on a mobile robot. In: International Conference on Intelligent Robots and Systems (2003)Google Scholar
  2. 2.
    Nakadai, K., Okuno, H., Kitano, H.: Realtime sound source localization and separation for robot audition. In: IEEE International Conference on Spoken Language Processing (2002)Google Scholar
  3. 3.
    Murray, J., Erwin, H., Wermter, S.: Auditory Robotic Tracking of Sound Sources using Hybrid Cross-Correlation and Recurrent Network. In: International Conference on Intelligent Robots and Systems (2005)Google Scholar
  4. 4.
    Amir, A., Handzel, B., Andersson, M., Krishnaprasad, P.S.: A Biomimetic Apparatus for Sound-source Localization. In: Proc. IEEE Conference on Decision and Control (2003)Google Scholar
  5. 5.
    Handzel, B., Shah, A.A., Krishnaprasad, V.: Robot phonotaxis with dynamic sound-source localization. In: IEEE International Conference on Robotics and Automation (2004)Google Scholar
  6. 6.
    Mumolo, E., Nolich, M., Vercelli, G.: Algorithms for acoustic localization based on microphone array in service robotics. In: Robotics and Autonomous Systems (2003)Google Scholar
  7. 7.
    Ureña, J., Hernández, A., Jiménez, A.: Advanced Sensorial System for an Acoustic LPS. Journal of Microprocessors and Microsystems (2006)Google Scholar
  8. 8.
    Munguia, R., Grau, A.: Delayed Feature Initialization for Inverse Depth Monocular SLAM. In: European Conference on Mobile Robots (2007)Google Scholar
  9. 9.
    Munguia, R., Grau, A.: Delayed Inverse Depth Monocular SLAM. In: 17th IFAC World Congress (2008)Google Scholar
  10. 10.
    Montiel, J.M.M., Civera, J., Davison, A.: Unified Inverse Depth Parametrization for Monocular SLAM. In: Robotics: Science and Systems Conference (2006)Google Scholar
  11. 11.
    Eade, E., Drummond, T.: Scalable monocular SLAM. In: IEEE Conference on Computer Vision and Pattern Recognition (2006)Google Scholar
  12. 12.
    Czyzewski, A.: Automatic identification of sound source position employing neural networks and rough sets. Pattern Recognition Letters 24 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Rodrigo Munguía
    • 1
  • Antoni Grau
    • 1
  1. 1.Department of Automatic ControlUPCBarcelonaSpain

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