Information-Driven Active Audio-Visual Source Localization
by , , ,
Abstract:
We present a system for sensorimotor audio-visual source localization on a mobile robot. We utilize a particle filter for the combination of audio-visual information and for the temporal integration of consecutive measurements. Although the system only measures the current direction of the source, the position of the source can be estimated because the robot is able to move and can therefore obtain measurements from different directions. These actions by the robot successively reduce uncertainty about the source's position. An information gain mechanism is used for selecting the most informative actions in order to minimize the number of actions required to achieve accurate and precise position estimates in azimuth and distance. We show that this mechanism is an efficient solution to the action selection problem for source localization, and that it is able to produce precise position estimates despite simplified unisensory preprocessing. Because of the robot's mobility, this approach is suitable for use in complex and cluttered environments. We present qualitative and quantitative results of the system's performance and discuss possible areas of application.
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PDF URL: http://dx.doi.org/10.1371/journal.pone.0137057
Reference:
Information-Driven Active Audio-Visual Source Localization (Niclas Schult, Thomas Reineking, Thorsten Kluss, Christoph Zetzsche), In PLoS ONE (Long Wang, ed.), Public Library of Science (PLoS), volume 10, 2015.
Bibtex Entry:
@Article{Schult2015,
  author    = {Schult, Niclas and Reineking, Thomas and Kluss, Thorsten and Zetzsche, Christoph},
  title     = {Information-Driven Active Audio-Visual Source Localization},
  journal   = {PLoS ONE},
  year      = {2015},
  volume    = {10},
  number    = {9},
  pages     = {e0137057},
  month     = {sep},
  abstract  = {We present a system for sensorimotor audio-visual source localization on a mobile robot. We utilize a particle filter for the combination of audio-visual information and for the temporal integration of consecutive measurements. Although the system only measures the current direction of the source, the position of the source can be estimated because the robot is able to move and can therefore obtain measurements from different directions. These actions by the robot successively reduce uncertainty about the source's position. An information gain mechanism is used for selecting the most informative actions in order to minimize the number of actions required to achieve accurate and precise position estimates in azimuth and distance. We show that this mechanism is an efficient solution to the action selection problem for source localization, and that it is able to produce precise position estimates despite simplified unisensory preprocessing. Because of the robot's mobility, this approach is suitable for use in complex and cluttered environments. We present qualitative and quantitative results of the system's performance and discuss possible areas of application.},
  doi       = {10.1371/journal.pone.0137057},
  editor    = {Long Wang},
  publisher = {Public Library of Science ({PLoS})},
  url       = {10.1371/journal.pone.0137057">http://dx.doi.org/10.1371/journal.pone.0137057},
}