Attentional Landmarks and Active Gaze Control for Visual SLAM

Simone Frintrop and Patric Jensfelt

Abstract:

This paper is centered around landmark detection, tracking and matching for visual SLAM (Simultaneous Localization And Mapping) using a monocular vision system with active gaze control. We present a system specialized in creating and maintaining a sparse set of landmarks based on a biologically motivated feature selection strategy. A visual attention system detects salient features which are highly discriminative, ideal candidates for visual landmarks which are easy to redetect. Features are tracked over several frames to determine stable landmarks and to estimate their 3D position in the environment. Matching of current landmarks to database entries enables loop closing. Active gaze control allows us to overcome some of the limitations of using a monocular vision system with a relatively small field of view. It supports (i) the tracking of landmarks which enable a better position estimation, (ii) the exploration of regions without landmarks to obtain a better distribution of landmarks in the environment, and (iii) the active redetection of landmarks to enable loop closing in situations in which a fixed camera fails to close the loop. Several real-world experiments show that accurate position estimation is obtained with the presented system and that active camera control outperforms the passive approach.

BibTeX Entry: 

@InProceedings{Frintrop08b,
  author =       {Simone Frintrop and Patric Jensfelt},
  title =        {Attentional Landmarks and Active Gaze Control for Visual {SLAM}},
  booktitle =    {IEEE Transactions on Robotics, special Issue on Visual {SLAM}},
  year =         2008,
  month =        oct,
  number =       5,
  volume =       24
}
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