Single Sound Source SLAM

  • Rodrigo Munguía
  • Antoni Grau
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)

Abstract

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.

Keywords

SLAM Sound Sources Bearing Sensors 

References

  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

Personalised recommendations